ETIC, AI Engineer - Senior Associate

Eligibility / Qualification Required:

• Key Responsibilities:
  • Design, develop, and optimize machine learning pipelines, including classical ML and deep learning models, using frameworks like scikit-learn, PyTorch, TensorFlow, and Hugging Face Transformers.
  • Lead development of retrieval-augmented generation (RAG) systems, integrating vector databases (e.g., FAISS, Weaviate, Qdrant) and frameworks like LangChain, LangGraph or LlamaIndex.
  • Fine-tune and adapt foundation models using techniques such as LoRA, PEFT, or instruction tuning for client-specific use cases.
  • Generate and evaluate synthetic data to support model robustness, augmentation, and privacy-aware training.
  • Build and expose AI models through RESTful APIs or microservices using FastAPI, Flask, or similar frameworks.
  • Ensure end-to-end model lifecycle tracking using tools like MLflow, Weights & Biases, or SageMaker Experiments.
  • Deploy models to cloud infrastructure (e.g., AWS, Azure, GCP) with attention to scalability, cost, and performance.
  • Collaborate with front-end developers and data teams to integrate AI features into products and platforms.
  • Review code, guide best practices in Git workflows, and contribute to team-level documentation and standards.
  • Communicate effectively with business stakeholders, translating complex AI concepts into actionable insights.
• Required Skills & Qualifications:
  • Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics or related technical field.
  • 3+ years of experience developing AI/ML solutions in production environments.
  • Strong programming skills in Python, with a proven track record using libraries like NumPy, Pandas, scikit-learn, PyTorch, and Transformers.
  • Hands-on experience with LLMs (e.g., GPT, LLaMA, Mistral), prompt engineering, and GenAI application development.
  • Experience building RAG pipelines, integrating with vector databases, and working with LangChain, LlamaIndex, or similar frameworks.
  • Experience with utilizing multi-modal data for training ML models and building AI applications.
  • Familiarity with fine-tuning models and optimizing performance for NLP or computer vision tasks.
  • Understanding of MLOps practices, including containerization (Docker), CI/CD workflows, and model monitoring.
  • Experience deploying models on cloud platforms like AWS SageMaker, Bedrock, GCP Vertex AI, or Azure AI Services.
  • Strong communication skills and experience working in Agile teams or consulting environments.
• Preferred Skills:
  • Experience with Cloud Services, storage blobs, virtual machines, etc.
  • Experience implementing LLM-based agents, chat applications, or autonomous workflows.
  • Exposure to tools like Kubernetes, Terraform, or Databricks.
  • Background in model evaluation, bias mitigation, explainability, and responsible AI practices.
  • Prior experience mentoring junior engineers or leading small project teams.
• Additional Skills (Required/Optional):
  • Accepting Feedback
  • Active Listening
  • Analytical Thinking
  • Business Analysis
  • Business Opportunities
  • Business Process Consulting
  • Business Process Improvement
  • Business Strategy
  • Business Transformation
  • Communication
  • Competitive Advantage
  • Competitive Analysis
  • Conducting Research
  • Consumer Behavior
  • Creativity
  • Customer Experience (CX) Strategy
  • Customer Insight
  • Customer Strategy
  • Data Analytics
  • Embracing Change
  • Emotional Regulation
  • Empathy
  • Go-to-Market Strategies
  • Inclusion
  • (and 14 more related skills)
• Travel Requirements: 0%
• Available for Work Visa Sponsorship? No
• Government Clearance Required? No

How to Apply: