As a AI Engineer, your role typically involves programming. You would be responsible for the commitments in terms of time, effort and quality of work. You would likely be a part of a larger offshore team and are expected to work collaboratively with your peers onsite and offshore to deliver milestone/sprint-based deliverables.
Typical activities that would be expected are
Program and deliver as per the scope provided by the delivery leads/onsite managers.
Actively participate in the discussions/scrum meetings to comprehend and understand your scope of work and deliver as per your estimates/commitments
Proactively reach out to others when you need assistance and to showcase your work
Work independently on your assigned work
Requirements
Should have experience in the below:
Python (Advanced proficiency)
PyTorch / TensorFlow (Model Development & Deployment)
LangChain / LlamaIndex (LLM Orchestration)
HuggingFace Transformers
OpenAI, AWS Bedrock, Vertex AI, or Azure OpenAI APIs
Vector Databases for RAG (Weaviate / Milvus / FAISS/mongodb)
MongoDB / PostgreSQL (Structured Data Retrieval & Joins)
Redis / DynamoDB (Fast Caching & Lookup)
Kafka / RabbitMQ (Message Queues for Real-Time Inference)
FastAPI / Flask (Backend APIs for ML Serving)
Docker (Containerization for Model Inference)
CI/CD Pipelines (GitHub Actions / GitLab CI / Jenkins)
MLflow / Weights & Biases (Experiment Tracking & Model Management)
S3 / GCS (Storage for Model Artifacts & Datasets)
ElasticSearch / OpenSearch (Search over structured/unstructured text)
Linting & Testing: Pytest, Black, Ruff, Flake8
Type Hinting, Documentation Standards, YAML/JSON Config Management
LLM training - finetuning (PEFT), pre-training
Should be familiar with at least two Gen AI platform like Amazon Bedrock, Copilot, Vertex, etc..
Should be familiar with at least two model like Claude, ChatGPT, Gemini, etc..
Should be familiar with RAG Model and Agentic AI model
Architectural Requirements:
Strong understanding of AI system design: data ingestion preprocessing model retrievalresponse
Experience leading teams on LLM/NLP/ML projects end-to-end
Excellent architectural decision-making & scalability mindset
Familiarity with prompt engineering, evaluation metrics, and benchmarking
Strong communication, documentation, and client-handling skills
Benefits
Insurance benefits for the self and the spouse, including maternity benefits.
Ability to work on many products as the organization is focused on working with several ISVs.
Monthly sessions to understand the directions of each function and an opportunity to interact with the entire hierarchy of the organization.
Celebrations are a common place - physical or virtual. Participate in several games with your coworkers.
Voice your opinions on topics other than your work - Chimera Talks.
* Hybrid working models - Remote + office
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