Roles & Responsibilities
- Role Overview We are looking for a Senior AI/ML Engineer with 5+ years of hands-on experience designing, building, and deploying machine learning and AI-driven systems in production. You will work across the full ML lifecycle from data pipelines and model development to deployment and monitoring - partnering closely with product, engineering, and client teams to deliver intelligent solutions that create measurable business impact.
- Design, develop, and deploy machine learning models and AI-driven features for production applications.
- Build and maintain data pipelines for training, evaluation, and inference, ensuring data quality and reproducibility.
- Fine-tune and integrate large language models (LLMs) and other foundation models into client-facing products.
- Design and implement retrieval-augmented generation (RAG) pipelines, vector search, and prompt engineering strategies.
- Develop and expose model inference APIs, ensuring low latency, scalability, and reliability.
- Collaborate with backend and mobile engineering teams to integrate AI capabilities into existing platforms.
- Establish MLOps practices, including model versioning, CI/CD for ML, and automated monitoring for drift and performance degradation.
- Evaluate model outputs for accuracy, bias, and safety, and implement guardrails where required.
- Optimize model performance, inference cost, and compute utilization across cloud environments.
- Stay current with emerging AI/ML research and tooling, and recommend adoption where it adds client value.
- Document architecture, experiments, and model decisions to support internal knowledge sharing and client delivery.
Required Skills
Must-have Skills
- Local candidates only (Must reside in/be local to Bangalore or Chennai).
- Finance, banking, or investment sector domain preferred. Exceptional Communication skills required.
- 5+ years of professional experience in machine learning, deep learning, or applied AI engineering.
- Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
- Hands-on experience working with LLMs (OpenAI, Anthropic, open-source models) via APIs or self-hosted deployment.
- Practical experience with RAG architectures, embeddings, and vector databases (e.g., Pinecone, Weaviate, FAISS, pgvector).
- Solid understanding of the ML lifecycle: data preprocessing, feature engineering, training, evaluation, and deployment.
- Experience deploying models as REST/GraphQL services using frameworks such as FastAPI or Flask.
- Familiarity with cloud AI/ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI).
- Working knowledge of containerization and orchestration (Docker, Kubernetes) for model deployment.
- Experience with MLOps tooling such as MLflow, Weights & Biases, or similar for experiment tracking.
- Strong understanding of prompt engineering, fine-tuning, and model evaluation techniques.
- Proficiency with Git-based version control and collaborative development workflows.
- Strong analytical and problem-solving skills, with the ability to work independently in a client-facing, fast-paced environment.
Nice-to-have Skills
- Experience with agentic AI frameworks (LangChain, LlamaIndex, or similar).
- Exposure to fine-tuning open-source LLMs and parameter-efficient techniques (LORA, QLORA).
- Familiarity with data engineering tools such as Airflow, Spark, or Kafka.
- Understanding of AI governance, responsible AI practices, and data privacy considerations.
- Prior experience in an AI consulting or client-delivery environment, managing multiple concurrent projects.
- Exposure to fintech, mobile, or cloud-platform domains.
Education & Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field or equivalent practical experience.
Ideal Candidate
- Finance, banking, or investment sector domain preferred.
- Local candidates only (Must reside in/be local to Bangalore or Chennai).
- Exceptional Communication skills required.
Perks & Benefits
- Medical insurance (for Self and family): Yes/No
- Vehicle Fuel Allowance: Yes/No
- Travel Allowance (outside city or state Travel): Yes/No
- Travel Dearness (manage daily expenses during Travel) Allowance: Yes/No
- Annual Performance Bonus: Yes/No
- Sales Incentive: Yes/No
- Festival Bonus: Yes/No
- Others (if any):