ML Engineer
4 weeks ago
Responsibilities:
Development, deployment, monitoring, and maintenance of data pipelines and machine learning models in a production environment.
Collaborate with data engineers, data scientists, and IT teams to resolve technical issues and optimize data and ML workflows.
Maintain detailed documentation for data and ML operations processes, configurations, and updates.
Project task management with team spread across onshore and offshore locations.
Ownership of Client communication – gathering requirements, problem structuring and delivery of output.
Keep up to date with new tools & tech in the market, create point of view on where they fit in the ML Operations scope and how they support the client architectures.
Build capabilities in junior team members.
Qualifications (Required):
3+ years of experience in developing and deploying machine learning models.
Hands-on experience in Python (intermediate to advanced) and SQL ( advanced)
Bachelor’s or master’s degree in economics, mathematics, computer science/engineering, operations research or related analytics areas
Extensive knowledge of ML tools and other services within Cloud Platforms .
Strong software development skills in Python
Experience with building data pipelines in Airflow (or similar programmable tools)
Understanding of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch, Kubeflow)
Familiarity with version control systems (e.g., Git), CI/CD tools (Jenkins, Concourse, Ansible, Chef, Puppet etc.) and containerization technologies (e.g., Docker, Kubernetes)
Excellent problem-solving and communication skills
Qualifications (Preferred):
Experience in Large Language Models (LLM) and prompt engineering.
Experience in OpenAI, Video Analytics, Audio Analytics.
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