253 Machine Learning Roles jobs in the Philippines
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Founded in 1994 and headquartered in Switzerland,
ERNI
is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team.
Why ERNI is the Perfect Place for You:
- International Exposure: Work with global clients on cutting-edge projects.
- Inclusive Culture: Thrive in a collaborative and diverse work environment.
- Career Development: Enjoy continuous learning and professional growth opportunities.
Perks And Benefits
- Career Stability: Enjoy a stable career path with ample project opportunities.
- Immediate Coverage: Private HMO and insurance benefits from day one.
- Jubilee Celebration: A 5-year milestone includes a complimentary trip to any European ERNI sites.
- Comprehensive Benefits: Government-mandated benefits including 13th-month pay.
- Skill Enhancement: Access free training and certifications.
- Wedding Gift: To celebrate your special day.
- Baby Basket: To welcome your newborn to the ERNI family.
- Fruit Basket: Boost of vitamins during hospitalization.
- Office Perks: Enjoy free snacks and coffee.
Growth And Opportunities
- Free Training: Advance your skills through technical and non-technical training.
- Challenging Projects: Engage in complex software projects across MedTech, Industry,
Finance, and Transportation.
- Supportive Environment: Benefit from a team dedicated to guiding and supporting your success.
- Recognition and Advancement: Receive acknowledgment for your efforts and
opportunities for promotion.
- Open Communication: Experience transparency and value your input in our culture.
Flexibility
- Hybrid Work Setup: Balance remote and in-person work for better work-life integration.
Events
- Connect and Celebrate: Participate in a variety of events including leisure, summer,
family, social, and year-end gatherings.
What Are Our Wishes
We are seeking a hands-on
MLOps / Machine Learning Engineer
with deep expertise in the
Azure Databricks
ecosystem to help build our AI/ML platform from the ground up. You will work collaboratively with a cross-functional team to implement a predefined architecture and establish the foundations of a production-grade system that adheres to strict data governance and compliance standards.
Because this is a greenfield build, the role combines MLOps and Machine Learning engineering responsibilities into a single, integrated position. You will contribute across the end-to-end ML lifecycle from data pipelines and governance through to model deployment and monitoring with a strong focus on collaboration. As the platform grows, you will help shape best practices and define clear processes, ensuring responsibilities remain focused and sustainable
- 5+ years of experience as an ML Engineer, MLOps Engineer, or similar hybrid role.
- Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Proven expertise in Azure Databricks, Azure ML, Data Factory, Delta Lake, and MLflow.
- Hands-on experience with Git for pipeline development (branching strategies, code reviews, version control best practices).
- Solid understanding of MLOps practices, CI/CD, and production ML requirements.
- Experience working under strict governance and compliance frameworks.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, or related field.
Preferred Qualifications
- Familiarity with Generative AI, LLM deployment, or RAG pipelines using Azure OpenAI Service, LangChain, or open-source LLMs.
- Experience with vector databases (e.g., FAISS, Milvus, Pinecone) and model explainability tools.
- Azure certifications (e.g., Azure Data Scientist Associate, Azure Solutions Architect, or Azure DevOps Engineer).
Soft Skills
- Curious and eager to learn — passionate about exploring new technologies and approaches.
- Collaborative mindset — thrives in a team environment and values collective success.
- Adaptable — comfortable in a role that spans both ML engineering and MLOps, with evolving responsibilities.
- Problem-solving skills — able to balance compliance requirements with practical implementation.
- Attention to detail — especially in governance, testing, and documentation.
- Proactive communicator — ensures alignment with teammates and stakeholders.
*How can you contribute to the team?
Platform & Pipeline Development *
- Collaborate with the team to implement the initial AI/ML architecture on Azure Databricks, setting up infrastructure and workflows.
- Design and build scalable, reproducible ML pipelines for data ingestion, feature engineering, training, testing, and deployment.
- Ensure version control and collaboration through Git-based workflows.
Model Lifecycle & MLOps
- Establish processes for automated model training, tuning, deployment, and monitoring using Databricks MLflow and Azure ML Pipelines.
- Define and manage model registries, versioning, and traceability.
Data Governance & Compliance
- Implement strict controls for data access, lineage, and security.
- Ensure all pipelines and models comply with regulatory requirements, auditability, and ML ethics standards.
- Embed compliance requirements into system design from day one.
Deployment & Monitoring
- Deploy models for real-time and batch inference using MLflow
- Contribute to monitoring frameworks for drift detection, latency, and performance degradation using Azure Monitor or equivalent.
CI/CD & Infrastructure
- Integrate pipelines with Azure DevOps or GitHub Actions for automated testing, validation, and deployment.
- Support infrastructure-as-code with Terraform, Bicep, or ARM templates to ensure reproducibility and scalability.
Collaboration & Documentation
- Partner with data scientists to productionize research prototypes.
- Document workflows, governance processes, and best practices for ongoing maintainability.
Switzerland
- Germany
- Spain
- Slovakia
- Romania
- Philippines
- Singapore
- USA
ERNI Development Center Philippines Inc.
, 9th Floor, Lica Malls Shaw, 500 Shaw Boulevard, 1555, Mandaluyong City, Philippines
| |
We deliberately focus on what we know best.
- 18 Locations in 8 Countries
- 800+ Employees across the Globe
- ISO Certified
Machine Learning Engineer
Posted today
Job Viewed
Job Description
What You'll Do
Domain‑Driven Model Development
- Lead end‑to‑end ML projects (predictive maintenance, golden‑batch optimization, fault‑detection) in manufacturing, energy, water and building contexts.
Data Engineering & Feature Work
- Ingest and preprocess time‑series sensor, PLC, and historian data.
- Engineer features for equipment health, process stability ("golden batch" profiles), energy/water efficiency.
Modeling & Deployment
- Build and validate models (classification/regression) using scikit‑learn, TensorFlow/PyTorch.
- Containerize and serve via TensorFlow Serving, ONNX Runtime or equivalent. Monitor model drift and retrain pipelines in production.
Cross‑Functional Collaboration
- Design and document APIs, message‑queue integrations (Kafka/RabbitMQ) for downstream apps.
Must‑Have Qualifications
Deep Industry Experience
- 3+ years in Manufacturing or relevant roles in Energy, Water or Building Automation.
- Hands‑on understanding of shop‑floor processes, PLC data, preventive vs. predictive maintenance.
ML Fundamentals
- Solid grasp of backpropagation, F1‑score vs. confusion‑matrix trade‑offs, over/under‑sampling.
Software & Data Skills
- Python: threading, async, type‑hints; familiar with pandas, NumPy.
- SQL: complex JOINs, GROUP BY, window functions.
- APIs & Queues: REST/gRPC design, Kafka or RabbitMQ.·
Deployment Frameworks
Experience with TensorFlow Serving or ONNX Runtime on Kubernetes or edge‑devices.
Bonus
- Computer Vision: OpenCV, image‑processing pipelines for visual inspection.
- Edge AI: Raspberry Pi, Jetson Nano or similar—optimizing models for constrained hardware.
What We're Looking For
- Domain‑First Mindset: You know that real impact comes from marrying hands‑on equipment knowledge with ML, not just toy datasets.
- Fast Learner: You'll upskill on new algorithms and tools via online courses and documentation—nothing holds you back.
- Collaborative Communicator: You can translate between data science jargon and operations speak.
- Product‑Obsessed: You see every ML experiment as a step toward a tangible solution for our clients.
Job Types: Full-time, Permanent
Benefits:
- Company Christmas gift
- Company events
- Flexible schedule
- Flextime
- Health insurance
- Life insurance
- Paid training
- Promotion to permanent employee
Work Location: In person
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team.
Why ERNI is the Perfect Place for You:
- International Exposure: Work with global clients on cutting-edge projects.
- Inclusive Culture: Thrive in a collaborative and diverse work environment.
- Career Development: Enjoy continuous learning and professional growth opportunities.
Perks and Benefits:
- Career Stability: Enjoy a stable career path with ample project opportunities.
- Immediate Coverage: Private HMO and insurance benefits from day one.
- Jubilee Celebration: A 5-year milestone includes a complimentary trip to any European ERNI sites.
- Comprehensive Benefits: Government-mandated benefits including 13th-month pay.
- Skill Enhancement: Access free training and certifications.
- Wedding Gift: To celebrate your special day.
- Baby Basket: To welcome your newborn to the ERNI family.
- Fruit Basket: Boost of vitamins during hospitalization.
- Office Perks: Enjoy free snacks and coffee.
Growth and Opportunities:
- Free Training: Advance your skills through technical and non-technical training.
- Challenging Projects: Engage in complex software projects across MedTech, Industry,
Finance, and Transportation.
- Supportive Environment: Benefit from a team dedicated to guiding and supporting your success.
- Recognition and Advancement: Receive acknowledgment for your efforts and
opportunities for promotion.
- Open Communication: Experience transparency and value your input in our culture.
Flexibility:
- Hybrid Work Setup: Balance remote and in-person work for better work-life integration.
Events:
- Connect and Celebrate: Participate in a variety of events including leisure, summer,
family, social, and year-end gatherings.
What are our wishes:
We are seeking a hands-on MLOps / Machine Learning Engineer with deep expertise in the Azure Databricks ecosystem to help build our AI/ML platform from the ground up. You will work collaboratively with a cross-functional team to implement a predefined architecture and establish the foundations of a production-grade system that adheres to strict data governance and compliance standards.
Because this is a greenfield build, the role combines MLOps and Machine Learning engineering responsibilities into a single, integrated position. You will contribute across the end-to-end ML lifecycle from data pipelines and governance through to model deployment and monitoring with a strong focus on collaboration. As the platform grows, you will help shape best practices and define clear processes, ensuring responsibilities remain focused and sustainable
- 5+ years of experience as an ML Engineer, MLOps Engineer, or similar hybrid role.
- Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Proven expertise in Azure Databricks, Azure ML, Data Factory, Delta Lake, and MLflow.
- Hands-on experience with Git for pipeline development (branching strategies, code reviews, version control best practices).
- Solid understanding of MLOps practices, CI/CD, and production ML requirements.
- Experience working under strict governance and compliance frameworks.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, or related field.
Preferred Qualifications
- Familiarity with Generative AI, LLM deployment, or RAG pipelines using Azure OpenAI Service, LangChain, or open-source LLMs.
- Experience with vector databases (e.g., FAISS, Milvus, Pinecone) and model explainability tools.
- Azure certifications (e.g., Azure Data Scientist Associate, Azure Solutions Architect, or Azure DevOps Engineer).
Soft Skills
- Curious and eager to learn — passionate about exploring new technologies and approaches.
- Collaborative mindset — thrives in a team environment and values collective success.
- Adaptable — comfortable in a role that spans both ML engineering and MLOps, with evolving responsibilities.
- Problem-solving skills — able to balance compliance requirements with practical implementation.
- Attention to detail — especially in governance, testing, and documentation.
- Proactive communicator — ensures alignment with teammates and stakeholders.
How can you contribute to the team?
Platform & Pipeline Development
- Collaborate with the team to implement the initial AI/ML architecture on Azure Databricks, setting up infrastructure and workflows.
- Design and build scalable, reproducible ML pipelines for data ingestion, feature engineering, training, testing, and deployment.
- Ensure version control and collaboration through Git-based workflows.
Model Lifecycle & MLOps
- Establish processes for automated model training, tuning, deployment, and monitoring using Databricks MLflow and Azure ML Pipelines.
- Define and manage model registries, versioning, and traceability.
Data Governance & Compliance
- Implement strict controls for data access, lineage, and security.
- Ensure all pipelines and models comply with regulatory requirements, auditability, and ML ethics standards.
- Embed compliance requirements into system design from day one.
Deployment & Monitoring
- Deploy models for real-time and batch inference using MLflow
- Contribute to monitoring frameworks for drift detection, latency, and performance degradation using Azure Monitor or equivalent.
CI/CD & Infrastructure
- Integrate pipelines with Azure DevOps or GitHub Actions for automated testing, validation, and deployment.
- Support infrastructure-as-code with Terraform, Bicep, or ARM templates to ensure reproducibility and scalability.
Collaboration & Documentation
Partner with data scientists to productionize research prototypes.
Document workflows, governance processes, and best practices for ongoing maintainability.
Switzerland · Germany · Spain · Slovakia · Romania · Philippines · Singapore · USA
ERNI Development Center Philippines Inc., 9th Floor, Lica Malls Shaw, 500 Shaw Boulevard, 1555, Mandaluyong City, Philippines
| |
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Position Title: Machine Learning Engineer
Salary: Open for discussion/negotiation
Mandatory Qualifications:
- Master's degree in Computer Science, Data Science, Machine Learning, or a related field. Ph.D. is a plus.
- 5+ years of experience in machine learning, data science, or a related field.
- Strong proficiency in programming languages such as Python, R, or Java.
- Extensive experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
- Proven track record of designing and deploying machine learning models in a production environment.
- Solid understanding of statistical methods, data analysis, and data preprocessing techniques.
- Experience with big data technologies and tools such as Hadoop, Spark, or similar.
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to think critically and creatively.
- Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment.
- Experience with natural language processing (NLP), computer vision, or other specialized areas of machine learning is a plus.
Desired Qualifications:
- Experience in Financial institution or Fintech company data analytics
- Publications or contributions to the machine learning community or production experience of product launch.
- Experience with ML Ops practices and tools.
Job Types: Full-time, Permanent
Work Location: In person
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Machine Learning Developer
We are looking for a skilled Machine Learning Developer to join our team. In this role, you'll be tasked with designing and implementing machine learning models to solve complex problems and enhance our applications' capabilities. You will work closely with data scientists and software developers to integrate AI functionalities seamlessly.
Responsibilities:
- Designing and developing machine learning and deep learning systems.
- Running machine learning tests and experiments to enhance model accuracy.
- Implementing appropriate ML algorithms to solve various tasks and improve application performance.
- Collaborating with data engineers to build data and model pipelines.
- Analyzing and visualizing data to drive insights and optimize performance.
- Staying updated with the latest machine learning technologies and methodologies.
- Ensuring that algorithms generate scalable and efficient solutions.
Requirements:
- Strong proficiency in Python (proficiency in C# and .NET is preferred).
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
- Knowledge of data structures, data modeling, and software architecture.
- Familiarity with cloud services (Azure, AWS, or Google Cloud) and their machine-learning tools is preferred.
- Ability to work with large data sets and understand complex algorithms.
- Strong analytical and problem-solving skills.
- Excellent English oral and written communication skills.
- Willingness to work on Pacific Standard Time (8:00 AM – 5:00 PM California Time).
- Must own a Laptop or Desktop (8GB RAM, Core i5 or above) with an internet connection of at least 10mbps.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
About Us
We're a fast-moving startup on a mission to revolutionize the call centre industry using the power of AI and Large Language Models. We're building intelligent systemsto enhance customer experience, supercharge agent performance, and drive operational excellence.
Through advanced conversational AI, we build systems that understand, adapt, and evolve with every conversation. Our platform powers decision-support tools and intelligent virtual agents helping call centers deliver faster, smarter, and more human customer service—where every interaction matters.
As an ML Engineer, you'll design, train, and deploy models that not only empower better decisions and agent experiences—but also power the core intelligence behind real-time conversations. If you're a self-starter with a passion for deploying ML at scale and know how to get your hands dirty with LLMs, we want you on our founding team.
What You'll Do
- Design, build, and deploy ML pipelines and LLM-powered applications from scratch.
- Fine-tune, prompt, and integrate state-of-the-art LLMs (e.g., OpenAI, LLaMA, Mistral).
- Apply advanced techniques like retrieval-augmented generation (RAG), tool use, and embedding search.
- Collaborate with product and engineering to build AI-driven features for real-world call centre use cases (e.g., agent coaching, auto summarization, sentiment analysis).
- Own experiments end-to-end — from hypothesis to deployment — with minimal supervision.
- Optimize model inference (latency, memory) for production-scale workloads.
- Set up scalable infrastructure for model training, evaluation, and continuous improvement.
- Help shape our ML/AI roadmap and contribute to technical strategy.
What We're Looking For
- 3+ years of experience as an ML Engineer
- Deep expertise in NLP and LLMs (e.g., transformers, LoRA, vector search, prompt engineering).
- Strong Python skills and hands-on experience with frameworks like Hugging Face Transformers, LangChain, OpenAI, PyTorch.
- Experience deploying ML models in production (e.g., APIs, containers, cloud-based services).
- Comfort working in early-stage/startup environments — fast pace, lots of ambiguity, high impact.
- Ability to work autonomously and make product-informed decisions with minimal oversight.
Bonus Points For
- Experience in or knowledge of the call centre / contact centre space.
- Familiarity with voice-to-text models, real-time analytics, or conversation intelligence.
- MLOps experience (e.g., model versioning, monitoring, CI/CD).
- Prior experience with vector databases (e.g., FAISS, Pinecone, Weaviate).
Why Join Us?
- Be part of a mission-driven startup from the ground up.
- Shape the future of AI in a high-impact, real-world industry.
- Work remotely with flexibility and autonomy.
- Competitive compensation
Job Type: Full-time
Work Location: Remote
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team.
Why ERNI is the Perfect Place for You:
- International Exposure: Work with global clients on cutting-edge projects.
- Inclusive Culture: Thrive in a collaborative and diverse work environment.
- Career Development: Enjoy continuous learning and professional growth opportunities.
Perks and Benefits:
- Career Stability: Enjoy a stable career path with ample project opportunities.
- Immediate Coverage: Private HMO and insurance benefits from day one.
- Jubilee Celebration: A 5-year milestone includes a complimentary trip to any European ERNI sites.
- Comprehensive Benefits: Government-mandated benefits including 13th-month pay.
- Skill Enhancement: Access free training and certifications.
- Wedding Gift: To celebrate your special day.
- Baby Basket: To welcome your newborn to the ERNI family.
- Fruit Basket: Boost of vitamins during hospitalization.
- Office Perks: Enjoy free snacks and coffee.
Growth and Opportunities:
- Free Training: Advance your skills through technical and non-technical training.
- Challenging Projects: Engage in complex software projects across MedTech, Industry,
Finance, and Transportation.
- Supportive Environment: Benefit from a team dedicated to guiding and supporting your success.
- Recognition and Advancement: Receive acknowledgment for your efforts and
opportunities for promotion.
Open Communication: Experience transparency and value your input in our culture.
Flexibility:
- Hybrid Work Setup: Balance remote and in-person work for better work-life integration.
Events:
- Connect and Celebrate: Participate in a variety of events including leisure, summer,
family, social, and year-end gatherings.
What are our wishes:
We are seeking a hands-on MLOps / Machine Learning Engineer with deep expertise in the Azure Databricks ecosystem to help build our AI/ML platform from the ground up. You will work collaboratively with a cross-functional team to implement a predefined architecture and establish the foundations of a production-grade system that adheres to strict data governance and compliance standards.
Because this is a greenfield build, the role combines MLOps and Machine Learning engineering responsibilities into a single, integrated position. You will contribute across the end-to-end ML lifecycle from data pipelines and governance through to model deployment and monitoring with a strong focus on collaboration. As the platform grows, you will help shape best practices and define clear processes, ensuring responsibilities remain focused and sustainable
- 5+ years of experience as an ML Engineer, MLOps Engineer, or similar hybrid role.
- Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Proven expertise in Azure Databricks, Azure ML, Data Factory, Delta Lake, and MLflow.
- Hands-on experience with Git for pipeline development (branching strategies, code reviews, version control best practices).
- Solid understanding of MLOps practices, CI/CD, and production ML requirements.
- Experience working under strict governance and compliance frameworks.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, or related field.
Preferred Qualifications
- Familiarity with Generative AI, LLM deployment, or RAG pipelines using Azure OpenAI Service, LangChain, or open-source LLMs.
- Experience with vector databases (e.g., FAISS, Milvus, Pinecone) and model explainability tools.
- Azure certifications (e.g., Azure Data Scientist Associate, Azure Solutions Architect, or Azure DevOps Engineer).
Soft Skills
- Curious and eager to learn — passionate about exploring new technologies and approaches.
- Collaborative mindset — thrives in a team environment and values collective success.
- Adaptable — comfortable in a role that spans both ML engineering and MLOps, with evolving responsibilities.
- Problem-solving skills — able to balance compliance requirements with practical implementation.
- Attention to detail — especially in governance, testing, and documentation.
- Proactive communicator — ensures alignment with teammates and stakeholders.
How can you contribute to the team?
Platform & Pipeline Development
- Collaborate with the team to implement the initial AI/ML architecture on Azure Databricks, setting up infrastructure and workflows.
- Design and build scalable, reproducible ML pipelines for data ingestion, feature engineering, training, testing, and deployment.
- Ensure version control and collaboration through Git-based workflows.
Model Lifecycle & MLOps
- Establish processes for automated model training, tuning, deployment, and monitoring using Databricks MLflow and Azure ML Pipelines.
- Define and manage model registries, versioning, and traceability.
Data Governance & Compliance
- Implement strict controls for data access, lineage, and security.
- Ensure all pipelines and models comply with regulatory requirements, auditability, and ML ethics standards.
- Embed compliance requirements into system design from day one.
Deployment & Monitoring
- Deploy models for real-time and batch inference using MLflow
- Contribute to monitoring frameworks for drift detection, latency, and performance degradation using Azure Monitor or equivalent.
CI/CD & Infrastructure
- Integrate pipelines with Azure DevOps or GitHub Actions for automated testing, validation, and deployment.
- Support infrastructure-as-code with Terraform, Bicep, or ARM templates to ensure reproducibility and scalability.
Collaboration & Documentation
Partner with data scientists to productionize research prototypes.
Document workflows, governance processes, and best practices for ongoing maintainability.
Switzerland · Germany · Spain · Slovakia · Romania · Philippines · Singapore · USA
ERNI Development Center Philippines Inc., 9th Floor, Lica Malls Shaw, 500 Shaw Boulevard, 1555, Mandaluyong City, Philippines
| | (email protected)
Be The First To Know
About the latest Machine learning roles Jobs in Philippines !
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Mandatory Qualifications
- Master's degree in Computer Science, Data Science, Machine Learning, or related field (Ph.D. is a plus).
- 5+ years of experience in machine learning, data science, or related field.
- Strong programming skills in Python, R, or Java.
- Extensive experience with ML frameworks: TensorFlow, PyTorch, scikit-learn, etc.
- Proven track record of designing and deploying ML models in production.
- Solid understanding of statistical methods, data analysis, and preprocessing techniques.
- Experience with big data tools (Hadoop, Spark, etc.).
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Excellent problem-solving, critical thinking, and communication skills.
- Experience in NLP, computer vision, or specialized ML domains is a plus.
Desired Qualifications
- Experience in financial institutions or fintech data analytics.
- Publications, open-source contributions, or participation in the ML research community.
- Experience with ML Ops practices and tools for scalable deployment and monitoring.
Job Types: Full-time, Permanent
Work Location: In person
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Gratitude Philippines is hiring a Full time Machine Learning Engineer role in Mandaluyong, NCR. Apply now to be part of our team.
Job summary:
- Flexible hours available
AI Machine Learning Engineer
Posted today
Job Viewed
Job Description
Job Title: AI Machine Learning Engineer
Job Set-Up: Remote
Job Type: Full Time Contractor / 30-50 hours a week
Work Hours: 4 AM – 1 PM Manila Time with 1 hour break
JOB DESCRIPTION
We are seeking a highly skilled AI Machine Learning Analyst (or Engineer) to spearhead our efforts in leveraging machine learning, prescriptive analytics, and sales-driving AI agents to accelerate digital transformation. This role focuses on developing intelligent AI solutions that not only analyze data but also prescribe actionable strategies to optimize sales performance and drive business growth. The ideal candidate will be at the forefront of AI innovation, transforming traditional data processes into automated, intelligent systems that align with our strategic objectives in a fast-evolving digital landscape.
RESPONSIBILITIES
- Conduct advanced data analysis using Python and SQL, applying machine learning algorithms to uncover insights that support sales-driving initiatives and prescriptive analytics projects.
- Create and maintain dynamic Power BI reports to visualize key performance metrics, incorporating prescriptive recommendations for stakeholders to enhance decision-making.
- Provide technical support to the Data Team, including developing, testing, and optimizing sales driving AI agents to automate routine tasks and boost operational efficiency.
- Collaborate with team members to identify and implement process improvements through AI powered data insights, emphasizing machine learning models for predictive and prescriptive outcomes.
- Manage the end-to-end AI automation lifecycle, from ideation and data preprocessing to deployment and continuous monitoring, with a focus on machine learning integration for digital transformation.
- Design, develop, and deploy AI models, including machine learning frameworks for prescriptive analytics, while collaborating with Business Sales Operations and Data Analytics Teams to align technical outputs with strategic sales goals and digital initiatives.
- Support an innovation culture through knowledge-sharing, contributing to enterprise-wide AI training programs that promote the adoption of machine learning, AI agents, and digital transformation strategies.
QUALIFICATIONS
- Bachelor's degree in Computer Science, Data Science, Statistics, or a related field; advanced degrees in Machine Learning or AI preferred.
- Proficiency in Python, SQL, and Power BI, with strong experience in machine learning libraries.
- Proven experience in data analysis, visualization, and prescriptive analytics, demonstrating the ability to drive sales through AI insights.
- Deep familiarity with AI concepts, including advanced machine learning techniques, data preprocessing, and the development of sales-driving AI agents.
- Strong analytical and problem-solving skills with keen attention to detail, particularly in applying AI for digital transformation.
- Ability to multitask in a fast-paced environment and communicate complex findings effectively to nontechnical stakeholders.
ABOUT SATELLITE TEAMS
Satellite Teams is a global professional employer organization with offices in the USA, the Philippines, Costa Rica, Mexico, and Poland. We provide full-time remote teams to leading companies in the U.S. across a wide range of industries including advertising and entertainment, health and beauty, financial services, real estate and property development. We take pride in having the best talent and providing exceptional employee experiences.
Job Type: Full-time
Pay: Php60, Php103,000.00 per month
Benefits:
- Flexible schedule
- Opportunities for promotion
- Paid training
- Promotion to permanent employee
- Work from home
Application Question(s):
- Do you have experience with Python, SQL, and Power BI?
- Do you have experience with AI Machine Learning?
- What is your email address?
- What is your contact no?
Work Location: Remote