Contract Position: AI/ML Engineer

Experience: 8 - 19 years
Max Experience: 19
Our client is a Palo Alto–based AI infrastructure and talent platform founded in 2018. It helps companies connect with remote software developers using AI-powered vetting and matching technology. Originally branded as the “Intelligent Talent Cloud,”enabled companies to “spin up their engineering dream team in the cloud” by sourcing and managing vetted global talent. In recent years, they have evolved to support AI infrastructure and AGI workflows, offering services in model training, fine-tuning, and deployment—powered by their internal AI platform, ALAN, and backed by a vast talent network. They reported $300 million in revenue and reached profitability. Their growth is driven by demand for annotated training data from AI labs, including major clients like OpenAI, Google, Anthropic, and Meta.
Job Description
Job Title: AI/ML Engineer
Location: Noida
Experience: 8+ yrs
Employment Type: Contract to hire
Work Mode: Hybrid
Notice Period: Immediate joiners
Roles & Responsibilities
Bachelor’s or master’s degree in Computer Science, Data Science, or a related technical discipline.
10+ years of overall software development experience, including 3+ years of hands-on experience in machine learning or AI application development, with a proven track record of delivering production-grade solutions.
Strong programming proficiency in Python, with demonstrated experience in API development using FastAPI or Flask.
Backend development experience in C# or Java is considered an added advantage.
Solid experience developing AI solutions within the AWS ecosystem, including hands-on use of services such as Amazon Bedrock, SageMaker, Lambda, API Gateway, and S3.
Practical knowledge and implementation experience with Large Language Models and Generative AI frameworks such as LangChain, LlamaIndex, or custom RAG architectures.
In-depth understanding of RAG systems, including embedding generation, document chunking, retrieval, ranking, and response synthesis.
Experience with vector databases such as Pinecone, FAISS, or OpenSearch, as well as text embeddings and prompt engineering, is an added advantage.
Strong understanding of cloud security, including OAuth 2.0-based authentication, IAM policies, secure API design, and data protection practices.
Familiarity with DevOps practices and tools, including CI/CD pipelines, Docker, and Infrastructure as Code tools such as CloudFormation, AWS CDK, or Terraform.
Proficiency in relational databases such as SQL and strong understanding of data modelling.
Solid grasp of machine learning algorithms and techniques, including deep learning architectures.
Skilled in data preprocessing, feature engineering, and data manipulation using modern data science tools and libraries.
Demonstrated experience working across the full AI/ML project lifecycle, from business requirements analysis to model deployment and productization.
Practical experience using AI-assisted engineering tools such as GitHub Copilot or similar capabilities to improve productivity, code quality, documentation, testing, and development efficiency.
Strong understanding of responsible AI usage in software and AI/ML engineering, including validation of AI-generated outputs, secure coding practices, data privacy, explainability, and adherence to enterprise standards.
Strong analytical and problem-solving skills, with a structured approach to debugging, model evaluation, performance tuning, and optimization.
Excellent communication and collaboration abilities, with experience working in cross-functional and agile teams.
People Skills
Ability to translate complex business problems into technical challenges that can be solved using data science, machine learning, and AI techniques.
Ability to communicate technical ideas, model outcomes, and AI/ML solution approaches effectively to non-technical audiences.
Ability to work effectively in a team-oriented environment.
Curious and open-minded attitude toward new approaches, technologies, and methodologies.
Strong ownership mindset with the ability to drive initiatives from concept through delivery.

Work arrangement
Hybrid