AI​/ML Engineers

Job Description:

AI/ML Engineer (2026)

We are looking for a highly skilled AI/ML Engineer to design, build, and deploy production‑grade AI systems. You will bridge the gap between data science and operational software, creating intelligent, scalable, and secure applications using cutting‑edge models (LLMs, GenAI) and traditional machine learning. You will focus on turning experimental models into reliable, high‑performance, real‑world solutions.

• Productionize ML/AI Models:
  Develop, containerize, and deploy machine learning models, including Deep Learning and GenAI, into production environments.
• Generative AI & LLMs:
  Implement Large Language Models (LLMs) using frameworks like Lang Chain/Llama Index, focusing on prompt engineering, RAG architectures, and fine‑tuning.
• MLOps Implementation:
  Automate CI/CD pipelines, model versioning (DVC), monitoring, and retrain pipelines using MLOps tools (MLflow, Kubeflow).
• System Architecture:
  Architect scalable, resilient, and secure AI infrastructure on cloud platforms (AWS, Azure, or GCP).
• Data Engineering:
  Collaborate on ETL pipelines to ensure high‑quality data ingestion, preprocessing, and feature engineering for model training.
• Model Optimization:
  Optimize inference engines (e.g., Triton, vLLM) for low‑latency, high‑performance model serving.
• Responsible AI:
  Ensure models are compliant with ethical guidelines, auditing for bias, and implementing Explainable AI (XAI) techniques.

• Education:
  
  Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related technical field.
• Experience:
  
  3+ years of experience in deploying ML models in production.
• Programming:
  Expert proficiency in Python (including libraries: Num Py, Pandas, Scikit‑learn, PyTorch/Tensor Flow).
• GenAI Stack:
  Experience with Hugging Face, Lang Chain, vector databases (Pinecone, Milvus), and LLM APIs.
• MLOps & Tools:
  Hands‑on experience with Docker, Kubernetes, MLflow, and CI/CD tools.
• Cloud Platforms:
  Proficiency with AWS Sage Maker, Azure ML, or Vertex AI.
• Database Knowledge:
  Strong skills in SQL and No
  
  SQL databases.