Job Description – Senior AI/ML Engineer
Job Summary
We are seeking a highly experienced Senior AI/ML Engineer with 13+ years of experience in designing, developing, deploying, and optimizing enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in Python, Machine Learning, Deep Learning, NLP, Generative AI, LLMs, MLOps, and Cloud platforms.
The candidate will work closely with Data Scientists, Software Engineers, Data Engineers, Product Managers, and business stakeholders to build scalable AI/ML solutions and production-grade machine learning systems.
Key Responsibilities
- Design, develop, and deploy scalable AI/ML models and applications for enterprise use cases.
- Develop machine learning pipelines covering data preparation, feature engineering, model training, validation, deployment, and monitoring.
- Build and optimize supervised and unsupervised machine learning models.
- Develop solutions using Deep Learning, NLP, Computer Vision, and Generative AI techniques.
- Design and implement LLM-based applications, including RAG, prompt engineering, embeddings, vector search, and AI agents.
- Fine-tune and evaluate large language models for specific business use cases.
- Develop production-ready AI/ML APIs and microservices using Python and frameworks such as FastAPI or Flask.
- Implement MLOps practices for model versioning, deployment, monitoring, and lifecycle management.
- Collaborate with Data Engineers to build reliable data pipelines and feature stores.
- Optimize model performance, scalability, latency, and cost.
- Conduct model evaluation, experimentation, A/B testing, and performance benchmarking.
- Monitor deployed models for accuracy, drift, bias, and performance degradation.
- Work with cloud-based AI/ML services and infrastructure.
- Perform code reviews and establish engineering standards and best practices.
- Mentor junior and mid-level AI/ML engineers.
- Communicate technical solutions and recommendations to senior leadership and business stakeholders.
Required Technical Skills
- 13+ years of experience in software engineering, data science, AI/ML engineering, or related fields.
- Strong programming experience in Python.
- Extensive experience with Machine Learning algorithms and frameworks.
- Strong experience with:
- Scikit-learn
- TensorFlow
- PyTorch
- Pandas
- NumPy
- Strong understanding of supervised, unsupervised, and reinforcement learning concepts.
- Experience with Deep Learning and Neural Networks.
- Strong knowledge of Natural Language Processing (NLP).
- Hands-on experience with Generative AI and Large Language Models (LLMs).
- Experience with:
- RAG (Retrieval-Augmented Generation)
- Prompt Engineering
- Embeddings
- Vector Databases
- Semantic Search
- LLM Evaluation
- Model Fine-Tuning
- Experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or FAISS.
- Strong knowledge of REST APIs and microservices.
- Experience with SQL and NoSQL databases.
- Strong understanding of data structures, algorithms, and software engineering principles.
MLOps & Cloud Skills
- Experience building and managing MLOps pipelines.
- Hands-on experience with MLflow, Kubeflow, Airflow, or similar platforms.
- Experience with Docker and Kubernetes.
- Experience with CI/CD tools and DevOps practices.
- Strong experience with one or more cloud platforms:
- AWS
- Microsoft Azure
- Google Cloud Platform (Google Cloud Platform)
- Experience with cloud AI/ML services such as:
- AWS SageMaker
- Azure Machine Learning
- Google Vertex AI
- Experience with model deployment, monitoring, logging, and observability.
Preferred Skills
- Experience with Generative AI architecture and enterprise LLM applications.
- Experience developing AI-powered chatbots and virtual assistants.
- Knowledge of Agentic AI and AI Agents.
- Experience with LangChain, LlamaIndex, or similar frameworks.
- Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, Llama, or other foundation models.
- Knowledge of responsible AI, model governance, security, and privacy.
- Experience with distributed computing frameworks such as Apache Spark.
- Experience with data engineering and large-scale data processing.
- Experience with Terraform and Infrastructure as Code.
- Experience working with enterprise-scale AI platforms.
Education
- Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field.
- Advanced degree or relevant AI/ML certifications is a plus.
Soft Skills
- Strong analytical and problem-solving abilities.
- Excellent communication and collaboration skills.
- Ability to work with technical and non-technical stakeholders.
- Strong leadership and mentoring capabilities.
- Ability to work in a fast-paced, Agile environment.
- Strong ownership and ability to drive projects from concept to production.
Preferred Domain Experience
- Banking & Financial Services
- Healthcare
- Insurance
- Retail & E-commerce
- Telecommunications
- Manufacturing
- Technology
- Supply Chain & Logistics
Keywords
AI/ML Engineer, Senior AI/ML Engineer, Machine Learning Engineer, Artificial Intelligence, Python, Machine Learning, Deep Learning, NLP, Generative AI, GenAI, LLM, Large Language Models, RAG, Prompt Engineering, LLM Fine-Tuning, AI Agents, Agentic AI, LangChain, LlamaIndex, OpenAI, Azure OpenAI, PyTorch, TensorFlow, Scikit-learn, MLflow, Kubeflow, MLOps, Docker, Kubernetes, AWS, Azure, Google Cloud Platform, SageMaker, Azure ML, Vertex AI, Vector Database, Pinecone, Weaviate, Milvus, FAISS, FastAPI, REST API, Microservices, SQL, NoSQL, Data Science, Model Deployment, Model Monitoring, CI/CD, DevOps.
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