Senior AI/ML Engineer – Job Description

Position: Senior AI/ML Engineer
Experience: 10+ Years
Job Type: W2 Contract 
Location: Open / Hybrid / Remote

Job Summary

We are looking for a highly experienced Senior AI/ML Engineer with 10+ years of software engineering and machine learning experience to design, develop, and deploy intelligent, scalable AI/ML solutions. The ideal candidate will have strong expertise in Python, machine learning, deep learning, Generative AI, NLP, cloud platforms, and data engineering, along with hands-on experience taking ML solutions from experimentation through production.

Key Responsibilities

• Design, develop, and deploy end-to-end machine learning and AI solutions for enterprise applications.

• Build and optimize predictive models using supervised, unsupervised, and deep learning techniques.

• Develop Generative AI applications using LLMs, RAG, embeddings, vector databases, and prompt engineering.

• Work with frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, and LlamaIndex.

• Develop NLP, text classification, recommendation, forecasting, and anomaly detection solutions as required.

• Build production-ready AI/ML services and integrate models with enterprise applications through REST APIs and microservices.

• Develop data preprocessing, feature engineering, model training, validation, and evaluation pipelines.

• Implement MLOps practices for model deployment, monitoring, versioning, and continuous improvement.

• Work with cloud-based AI/ML services across AWS, Azure, or Google Cloud Platform.

• Collaborate with data engineers, software engineers, architects, product teams, and business stakeholders.

• Optimize models for scalability, performance, accuracy, latency, and cost.

• Establish responsible AI practices including model monitoring, security, governance, and explainability.

• Mentor junior engineers and contribute to technical architecture and engineering best practices.

Required Skills

• 10+ years of experience in software engineering, data science, machine learning, or AI engineering.

• Strong programming experience with Python.

• Hands-on expertise in Machine Learning and Deep Learning.

• Strong knowledge of NLP, Generative AI, LLMs, and transformer-based models.

• Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation.

• Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, or LlamaIndex.

• Strong understanding of SQL and experience working with large datasets.

• Experience developing and deploying REST APIs / microservices for AI/ML applications.

• Hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.

• Experience with Docker, Kubernetes, Git, CI/CD, and cloud deployment.

• Understanding of MLOps, model lifecycle management, monitoring, and model versioning.

• Strong knowledge of data structures, algorithms, software design principles, and scalable system architecture.

Preferred Skills

• Experience with Azure OpenAI, AWS Bedrock, Amazon SageMaker, Azure Machine Learning, or Vertex AI.

• Experience with FAISS, Pinecone, Azure AI Search, OpenSearch, Milvus, or similar vector databases.

• Knowledge of Kafka, Spark, Databricks, Snowflake, or modern data platforms.

• Experience building AI agents, Agentic AI, tool calling, and multi-agent systems.

• Familiarity with LangGraph, Semantic Kernel, MCP, or similar agent frameworks.

• Experience with model fine-tuning, LoRA/QLoRA, and open-source LLMs.

• Knowledge of AI security, responsible AI, data privacy, and governance.

• Experience working in Agile/Scrum environments.

Education

Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field.

Ideal Candidate

The ideal candidate is a hands-on senior engineer who can bridge AI/ML research, software engineering, data engineering, and production deployment. They should be capable of independently designing enterprise AI solutions while also contributing to architecture, technical leadership, and mentoring.