Machine Learning Engineer

4 days ago

Bangalore, India Recro Full time

Our Client is looking for Proficient in Python, TensorFlow, PyTorch, scikit-learn, Pandas; experienced in AI and ML model development, integration, deployment; familiar with Docker, Kubernetes, CI/CD tools, AWS/Azure/GCP; strong in data structures, algorithms, system design; and knowledgeable in SQL, PostgreSQL, and NoSQL databases.

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.

Requirements:

  • Education: Bachelors or Masters in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
  • 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.
  • The 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.

Proficient in Python, TensorFlow, PyTorch, scikit-learn, Pandas; experienced in AI and ML model development, integration, deployment; familiar with Docker, Kubernetes, CI/CD tools, AWS/Azure/GCP; strong in data structures, algorithms, system design; and knowledgeable in SQL, PostgreSQL, and NoSQL databases.

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