Machine Learning Engineer

ML Engineer

Experience: 4-7 Years

Location: Bangalore

Type: Full-time

Responsibilities

Model Development and Integration: Design, implement, test, integrate and deploy scalable

machine learning models, integrating them into production systems and APIs to support existing

and new customers.

Experimentation and Optimization: Lead the design of experiments and hypothesis testing for

product feature development; monitor and analyze model performance and data accuracy,

making improvements as needed.

Cross-Functional Collaboration: Work closely with cross-functional teams across India and the

US to identify opportunities, deploy impactful solutions, and effectively communicate findings to

both technical and non-technical stakeholders.

Mentorship and Continuous Learning: Mentor junior team members, contribute to knowledge

sharing, and stay current with best practices in data science, machine learning, and AI.

Qualifications

Education: Bachelors or Masters in Statistics, Mathematics, Computer Science, Engineering, or

a related quantitative field.

Experience:

4-7 years of experience building and deploying machine learning models.

Strong problem-solving skills with an emphasis on product development.

Experience operating and troubleshooting scalable machine learning systems in the

cloud.

Technical Skills:

Programming and Frameworks: Proficient in Python with experience in TensorFlow,

PyTorch, scikit-learn, and Pandas; familiarity with Golang is a plus; proficient with Git and

collaborative workflows.

Software Engineering: Strong understanding of data structures, algorithms, and system

design principles; experience in designing scalable, reliable, and maintainable systems.

Machine Learning Expertise: Extensive experience in AI and machine learning model

development, including large language models, transformers, sequence models, causal

inference, unsupervised clustering, and reinforcement learning. Knowledge of prompting

techniques, embedding models and RAG.

Innovation in Machine Learning: Ability to design and conceive novel ways of problem

solving using new machine learning models.

Integration, Deployment, and Cloud Services: Experience integrating machine

learning models into backend systems and APIs; familiarity with Docker, Kubernetes,

CI/CD tools, and Cloud Services like AWS/Azure/GCP for efficient deployment.

Data Management and Security: Proficient with SQL and experience with PostgreSQL;

knowledge of NoSQL databases; understanding of application security and data

protection principles.

Methodologies and Tools:

Agile/Scrum Practices: Experience with Agile/Scrum methodologies.

Project Management Tools: Proficiency with Jira, Notion, or similar tools.

Soft Skills:

Excellent communication and problem-solving abilities.

Ability to work independently and collaboratively.

Strong organizational and time management skills.

High degree of accountability and ownership.

Nice-to-Haves

Experience with big data tools like Hadoop or Spark.

Familiarity with infrastructure management and operations lifecycle concepts.

Experience working in a startup environment.

Contributions to open-source projects or a strong GitHub portfolio.