Were Hiring AI/ML Professionals

20+ Openings | 1 - 10 Years Experience | Multiple Locations | Multiple Levels

Location and work model may vary depending on the project and position.

Employment Type: Full-Time | Permanent

Industry: Fortune 500 Client Projects

About the role

We are looking for talented AI/ML professionals across different experience levels to design, develop, implement, deploy and manage intelligent applications using Artificial Intelligence, Machine Learning, Deep Learning, Generative AI and cloud technologies.

The roles span the complete AI engineering lifecycle, including data preparation, model development, training, evaluation, deployment, monitoring, optimization and enterprise integration. Depending on the position and project requirements, candidates may work on predictive machine learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), Computer Vision, Agentic AI, cloud-based AI solutions and MLOps/LLMOps.

Candidates are expected to demonstrate technical expertise appropriate to their experience level, ranging from foundational programming and ML skills to advanced solution architecture, technical leadership, team management and AI strategy.

Open Positions

1 - 4 Years: Junior AI/ML Engineer

3 - 7 Years: AI Engineer

6 - 10 Years: Senior / Lead AI Engineer

Job Title: Junior AI/ML Engineer

Experience: 1 - 4 Years

Job Summary

We are looking for a Junior AI/ML Engineer with hands-on experience in Python programming, machine learning fundamentals, data processing and AI application development. The candidate will work with senior engineers to develop, test, evaluate and deploy AI/ML solutions.

Key Responsibilities

Prepare, clean and analyze datasets for AI/ML applications.
Develop, train and evaluate machine learning models.
Implement classification, regression and clustering algorithms.
Perform feature engineering and model performance analysis.
Integrate ML models with applications using REST APIs.
Support cloud deployment, testing and troubleshooting.
Collaborate with data scientists, software developers and senior engineers.

Mandatory Skills

Python programming.
Pandas, NumPy and SQL.
Machine learning algorithms and fundamentals.
Scikit-learn and model evaluation metrics.
Statistics, data preprocessing and feature engineering.
Git and REST API fundamentals.
Basic exposure to AWS, Azure or GCP.

Good to Have

PyTorch or TensorFlow.
FastAPI or Flask.
Docker and basic CI/CD.
Basic Generative AI, LLM and prompt engineering knowledge.
Exposure to cloud-based AI services.

Job Title: AI Engineer

Experience: 3 7 Years

Job Summary

We are looking for an AI Engineer with hands-on experience in developing, deploying and optimizing AI/ML solutions. The candidate should have strong Python programming skills, practical knowledge of machine learning and deep learning, and experience integrating AI applications with cloud platforms. Depending on project requirements, the role may involve predictive ML, Generative AI, LLM applications, NLP or computer vision.

Key Responsibilities

Design, develop and deploy AI/ML models and applications.
Build data processing, feature engineering and model training pipelines.
Evaluate models and optimize accuracy, performance and reliability.
Develop AI-powered applications and integrate models through APIs.
Implement LLM-based solutions, RAG pipelines and semantic search where required.
Deploy AI applications using AWS, Azure or GCP.
Monitor production performance and troubleshoot technical issues.
Collaborate with product, data engineering and software development teams.

Mandatory Skills

Strong Python programming and SQL.
Machine learning algorithms, feature engineering and model evaluation.
Scikit-learn and practical experience with PyTorch or TensorFlow, as relevant.
REST APIs and FastAPI or Flask.
Hands-on experience with at least one cloud platform: AWS, Azure or GCP.
Git, Docker and basic CI/CD.
Experience developing and deploying AI/ML applications.

Generative AI Skills

LLMs such as GPT, Claude, Gemini or open-source models.
Prompt engineering and LLM API integration.
Embeddings and vector databases.
RAG architecture and frameworks such as LangChain or LlamaIndex.
LLM evaluation and response quality optimization.

Good to Have

AWS SageMaker, Amazon Bedrock, Azure Machine Learning or Google Vertex AI.
MLflow, model monitoring and automated pipelines.
Kubernetes and cloud deployment.
Fine-tuning, NLP, computer vision or Agentic AI.

Job Title: Senior / Lead AI Engineer

Experience: 6 – 10 Years

Job Summary

We are seeking a Senior / Lead AI Engineer to design, build and productionize scalable AI/ML and Generative AI solutions. The ideal candidate should have strong software engineering expertise, hands-on experience deploying AI solutions in production, and the ability to own technical implementation from design through deployment.

Key Responsibilities

3 - 5 Years of relevant experience in AI Technology
Lead end-to-end development of AI/ML and GenAI applications.
Design scalable model training, inference and deployment pipelines.
Develop LLM applications, RAG solutions and intelligent workflows where required.
Optimize model performance, inference latency, reliability and operational costs.
Implement evaluation, monitoring, observability and troubleshooting mechanisms.
Integrate AI services with enterprise applications, databases and APIs.
Establish engineering standards for testing, deployment and production readiness.
Mentor junior engineers and participate in technical design reviews.

Mandatory Skills

Advanced Python and software engineering fundamentals.
Strong hands-on expertise in ML, deep learning or Generative AI.
Production deployment experience on AWS, Azure or GCP.
REST APIs, Docker and CI/CD.
Model evaluation, monitoring and performance optimization.
Experience developing scalable, secure and reliable AI applications.
Strong debugging and system integration skills.

GenAI / Agentic AI Skills — For Relevant Openings

LLMs, prompt engineering, embeddings and RAG.
Vector databases, semantic search and reranking.
LangChain, LangGraph, LlamaIndex or equivalent frameworks.
Tool calling, workflow orchestration and state management.
LLM evaluation, guardrails, tracing and failure recovery.
LLMOps, inference optimization and cost management.

Good to Have

Kubernetes and Terraform.
MLflow, model registries and automated retraining.
MCP integrations and multi-agent workflows.
Fine-tuning and open-source model serving.
Experience mentoring engineers or leading technical workstreams.

Summary

Full Stack Developer

AI Agent Developer (LangGraph and MCP)

AI/ML Engineer – Agentic Systems

AI/ML Professionals

AI Engineer Intern

Applied ML / AI Engineer

See also