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AI/ML Engineer
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- Posted a day ago
- Be among the first 10 applicants
Job Description
About The Role
You will own model lifecycle from feature design through deployment and monitoring.
What You Will Do
You will own model lifecycle from feature design through deployment and monitoring.
What You Will Do
- Build ML pipelines and models.
- Deploy and monitor model behavior in production.
- Collaborate with data and platform teams for robust delivery.
- 3+ years in applied ML with production deployments.
- Strong Python and ML framework proficiency.
- MLOps literacy and statistical grounding.
- LLM and RAG deployment patterns.
- BFSI or healthcare AI domain exposure.
More Info
About Company
Skills:
Express, PostgreSQL, Dynamodb, Node.js, API design, Microservices, Django, React, Docker, MySQL, Cloud Infrastructure, Flask, MongoDB, FastAPI, Azure, Kubernetes, Python, agentic AI frameworks, RAG patterns, prompt engineering, Next.js
Skills:
BigQuery, Dataproc, Sql, Jenkins, Cloud Storage, Terraform, Sonarqube, DataFlow, Python, Logging, Cloud Functions, Cloud Build, Cloud Monitoring, GitHub Enterprise, Pub Sub, GitHub Actions, Cloud Run, Dataplex, Vertex AI
Skills:
Ooad, Cnn, Deep Learning, Tensorflow, Uml, Pytorch, Design Patterns, Opencv, Keras, Python, Computer Vision, LSTM, INT8, TensorRT, GRU, ResNet, ONNX, FP16, YOLO, RCNN, VGG, model quantization
Skills:
Tensorflow, Jax, Pytorch, Python, Generative AI solutions, LLM orchestration tools, NLP models, MLOps workflows
Skills:
workflow engines , Python, tool function calling, tracing observability tooling, Logfire, AI systems in production, prompting, Temporal, OpenTelemetry, pydantic-ai, LiteLLM, MCP, agent architectures