AI Machine Learning Engineer

Job Description

We are seeking a skilled AI / Machine Learning Engineer to design, build, and deploy scalable machine learning and Generative AI solutions. The role involves close collaboration with data scientists, software engineers, and product teams to transform data into actionable insights and integrate AI capabilities into production-grade applications.

🚀 Key Responsibilities

Machine Learning & GenAI Development

• Design, develop, and own end-to-end ML and Generative AI workflows, including:
  • Data ingestion and preprocessing
  • Model training, evaluation, deployment, and inference
• Build production-ready GenAI systems, including:
  • API design
  • Data pipelines
  • Orchestration, monitoring, scalability, and performance optimization

NLP & RAG Systems

• Design and implement multi-step RAG (Retrieval-Augmented Generation), agentic, and tool-augmented workflows using Python, LangChain, LangGraph, or similar frameworks.
• Lead NLP and text-processing pipelines, including:
  • Document parsing and text cleaning
  • Normalization and chunking strategies
  • Embeddings, metadata enrichment, and retrieval optimization
• Build, optimize, and maintain RAG pipelines using vector databases such as:
  • FAISS
  • AWS OpenSearch

Engineering & Integration

• Develop and integrate backend services and APIs (e.g., FastAPI) to expose AI/ML capabilities.
• Collaborate with engineering, product, and platform teams to deliver scalable AI-driven applications.
• Write, review, and maintain high-quality, testable, and maintainable code following best software engineering practices.
• Perform unit testing, integration testing, and system validation to ensure reliability and robustness.
• Diagnose and resolve performance, scalability, and reliability issues across environments.

🧩 Collaboration & Delivery

• Ensure strong alignment between business requirements and delivered AI features.
• Actively participate in Agile development processes and cross-functional collaboration.
• Manage multiple workstreams, including application development, GenAI systems, and ML research.

🎓 Education & Experience

Education

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or related field.

Experience

• 4.5+ years of professional experience as:
  • Machine Learning Engineer
  • AI Engineer
  • Software Engineer working on AI-driven systems

🛠️ Technical Skills

Core Skills

• Advanced proficiency in Python
• Strong experience with ML libraries:
  • NumPy, Pandas, scikit-learn
  • TensorFlow or PyTorch
• Mandatory NLP and text-processing experience, including:
  • Document processing
  • Embeddings
  • Retrieval strategies
  • LLM-based workflows

Generative AI & MLOps

• Hands-on experience with:
  • Generative AI and LLM systems
  • RAG, agents, prompt engineering
  • Orchestration frameworks (LangChain, LangGraph, or similar)
• Understanding of MLOps best practices, including:
  • Model deployment
  • Monitoring and versioning
  • Lifecycle management
• Experience with testing frameworks:
  • MLflow, PyTest, or similar

Cloud & DevOps (Mandatory)

• Strong hands-on experience with AWS or Azure (at least one required)

AWS:

• Lambda, S3, ECS, SageMaker, Step Functions

Azure:

• Azure OpenAI, Azure Functions, Storage, App Services
• Experience with REST APIs, CI/CD pipelines, and tools such as:
  • Git
  • Jenkins, GitHub Actions, or similar

🌟 Soft Skills & Attributes

• Strong problem-solving and analytical thinking
• Excellent communication and collaboration skills
• Ability to work under pressure and manage tight deadlines
• Flexibility to switch between multiple projects and priorities

📜 Additional Requirements

• Valid driver’s license
• Ability to obtain necessary travel documentation for international assignments

🔑 Key Skills

• Machine Learning
• Python
• NLP & Metadata
• Application Development
• Unit & Integration Testing
• Monitoring & Performance Management
• Information Technology