Senior AI/ML Engineer – Job Description
Position: Senior AI/ML Engineer
Experience: 10+ Years
Job Type: W2 Contract
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.
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