--This is an ONSITE Role. Please apply only if you can come to office----This is NOT a New College Gradate role-------------------------------------Minimum of8 years of work expneeded--------------------------------About UsWe are a forward-thinking organization focused on leveraging artificial intelligence and machine learning to create impactful, scalable solutions. Our projects involve cutting-edge technologies such as Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG), offering exciting opportunities to work at the forefront of innovation. Join us to help shape the future of intelligent systems!
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:●Minimum of 8 years of work experience with hast 4 years 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.
