Machine Learning Engineer

Role Overview

We are seeking a skilled Machine Learning Engineer to design, develop, and deploy advanced AI/ML models, with a focus on Generative AI, RAG architectures, and large-scale machine learning applications. You will work on end-to-end ML pipelines, integrating state-of-the-art tools like OpenAI, Anthropic Claude, and vector databases to deliver high-quality solutions for real-world business challenges.

Key Responsibilities

● Machine Learning, Generative AI & RAG Development:

● Build and fine-tune large language models (LLMs) using frameworks such as OpenAI GPT or Anthropic Claude.

● Design and implement RAG pipelines for scalable, real-time applications leveraging vector databases like Pinecone, Weaviate, Opensearch.

● Develop prompt engineering strategies to optimize model outputs for specific use cases.

● Design and deploy scalable ML models that integrate with existing systems.

● End-to-End ML Pipeline:

● Architect, train, and deploy machine learning pipelines for NLP and multimodal AI solutions.

● Conduct data preprocessing, feature engineering, and exploratory data analysis for training datasets.

● Optimize embeddings for semantic search and document retrieval tasks.

● Model Deployment & Optimization:

● Deploy ML models in production environments using cloud platforms like AWS SageMaker, ECS or equivalent tools.

● Ensure scalability, reliability, and low latency in production systems while monitoring model performance.

● Implement CI/CD pipelines for ML models using Docker, Kubernetes, MLflow.

● Ensure APIs and ML services handle high traffic with minimal latency.

● Security & Compliance:

● Ensure ML APIs follow best practices for authentication, authorization, and data privacy.

● Collaboration & Integration:

● Work closely with cross-functional teams including data scientists, software engineers, and product managers to align ML solutions with business objectives.

● Work with data engineers to design feature stores and streaming pipelines.

● Integrate ML outputs into enterprise systems while ensuring seamless user experiences.

● Research & Innovation:

● Stay updated on advancements in generative AI, LLMs, embeddings, and RAG technologies to enhance existing systems.

● Experiment with new algorithms and frameworks to drive innovation in AI-powered applications.

Required Skills & Qualifications

● Technical Expertise:

● Proficiency in Python; familiarity with frameworks like PyTorch, TensorFlow, and libraries like Hugging Face Transformers.

● Hands-on experience with LLMs (e.g., OpenAI GPT models, Anthropic Claude) and fine-tuning techniques.

● Strong understanding of RAG architectures and vector database integration (e.g., Opensearch, Pinecone, Weaviate).

● API Development: FastAPI, Flask, Django

● Containerization: Docker, AWS ECS, Kubernetes

● Cloud & Data Tools:

● Experience with cloud platforms such as AWS (SageMaker preferred), GCP Vertex AI, or Azure ML for deploying ML models.

● Familiarity with SQL or NoSQL databases for data extraction and preprocessing tasks.

● Problem-Solving Skills:

● Ability to design scalable solutions for complex problems involving unstructured data and large datasets.

● Strong analytical skills with a focus on optimizing ML workflows for performance and efficiency.

● Soft Skills:

● Excellent communication skills to collaborate effectively with technical and non-technical stakeholders.

● A passion for learning and staying ahead in the rapidly evolving field of artificial intelligence.

Preferred Qualifications

● Experience building conversational AI systems or chatbots using generative AI technologies.

● Experience with building REST API using frameworks such as Fast API.

● Experience with SQL and NoSQL database/store (Postgres, DynamoDB, Opensearch etc.)

● Knowledge of NLP techniques such as sentiment analysis, topic modeling, or summarization tasks.

● Familiarity with serverless architectures (e.g., AWS Lambda) or ECS for scalable ML deployment.

● Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or related fields.