Roles & Responsibilities
We are seeking a skilled AI Engineer with strong expertise in Machine Learning (ML) and Generative AI (GenAI) to design, build, and deploy intelligent AI solutions. The role requires hands-on experience across the AI lifecycle, including data preparation, model development, fine-tuning, integration, deployment, and monitoring of production-grade AI systems.The ideal candidate is a pragmatic problem solver who can translate functional requirements into robust AI implementations and work closely with data engineers, architects, and platform teams in a cloud-native environment.________________________________________Key ResponsibilitiesAI / ML & Generative AI Development
- Design, develop, and optimize ML models for use cases such as classification, summarization, recommendation, content generation, and semantic search.
- Build and integrate Generative AI solutions using Large Language Models (LLMs) for tasks such as text generation, summarization, Q&A, conversational interfaces, and structured content creation.
- Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector search.
- Fine-tune and adapt pre-trained models (e.g., GPT-family models, LLaMA, Falcon, Stable Diffusion) using techniques such as LoRA / QLoRA, prompt tuning, and instruction tuning.
- Perform feature engineering, hyperparameter tuning, and systematic model evaluation.
Data Handling & AI Pipelines
- Work with both structured and unstructured data (documents, text, metadata, multimedia descriptors).
- Build and maintain data pipelines for model training, inference, and evaluation in collaboration with data engineering teams.
- Implement and manage vector databases (e.g., FAISS, Pinecone, Weaviate, OpenSearch) to support semantic retrieval and RAG workflows.
- Ensure data quality, consistency, and traceability across AI pipelines.
Model Deployment & MLOps
- Package and deploy AI/GenAI models using Docker and cloud-native deployment patterns.
- Build scalable inference services using APIs and serving frameworks such as FastAPI, TorchServe, or equivalent.
- Implement monitoring for model performance, latency, and quality, including drift detection and retraining workflows.
- Integrate CI/CD pipelines to support repeatable and reliable AI model deployments.
- Collaborate with platform teams to ensure solutions meet security, scalability, and reliability standards.
Collaboration & Continuous Improvement
- Collaborate with cross-functional teams to translate functional and technical requirements into AI-driven solutions.
- Participate in design discussions, code reviews, and technical documentation.
- Continuously improve AI workflows, prompts, evaluation strategies, and deployment practices.
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Required Skills & Experience
Education & Background
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- 4–8 years of hands-on experience in AI / ML engineering roles.
Core Technical Skills
- Strong proficiency in Python for AI/ML and GenAI development.
- Hands-on experience with ML frameworks and libraries such as Scikit-learn.
- Strong experience with LLMs, transformers, embeddings, and RAG pipelines.
- Proficiency with frameworks such as LangChain, LangGraph, LlamaIndex, and Hugging Face Transformers.
- Experience with prompt engineering, prompt optimization, and LLM fine-tuning.
- Solid understanding of algorithms, statistics, optimization techniques, and model evaluation metrics.
- Practical experience in NLP and Generative AI techniques; exposure to multimodal AI is a plus.
Cloud & MLOps
- Experience working with AWS-based AI/ML services and cloud-native architectures.
- Hands-on experience with Docker, Kubernetes (basic to intermediate), and CI/CD pipelines.
- Familiarity with MLOps tools such as MLflow, Kubeflow, or similar platforms.
Professional Skills
- Strong problem-solving, debugging, and performance optimization skills.
- Ability to write clean, modular, and production-grade code.
- Good communication skills and ability to work effectively in cross-functional teams.
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Nice-to-Have Skills
- Exposure to RLHF, multi-agent systems, or agentic AI frameworks.
- Experience with evaluation frameworks for GenAI outputs.
- Knowledge of ethical AI, bias detection, explainability, and governance concepts.
- Familiarity with vector search optimization and cost-efficient inference strategies.
Experience
Skills
- Primary Skill: AI/ML Development
- Sub Skill(s): AI/ML Development
- Additional Skill(s): AI/ML Development, TensorFlow, NLP, Pytorch
About The Company
Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley. We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence. We accelerate experience-led transformation in the delivery of digital platforms. Infogain is also a Microsoft (NASDAQ: MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP).Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Kraków, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.
