Pibit.AI-Machine Learning Engineer
Job Title: Machine Learning Engineer-2
Location : Bangalore
Exp : 2+ Years
Position Overview
As a Machine Learning Engineer, you will design, implement, and optimize AI
solutions while ensuring model success. You will lead the ML lifecycle from
development to deployment, collaborate with cross-functional teams, and enhance
AI capabilities to drive innovation and impact.
Key Responsibilities:
Design and implement AI product features.
Maintain and optimize existing AI systems.
Train, evaluate, deploy, and monitor ML models.
Design ML pipelines for experiment, model, and feature management.
Implement A/B testing and scalable model inferencing APIs.
Optimize GPU architectures, parallel training, and fine-tune models for
improved performance.
Deploy LLM solutions tailored to specific use cases.
Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and
orchestration frameworks.
Technical Requirements:
LLM & ML: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama
LLMOps: MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex,
SageMaker, AWS Bedrock, Azure AI
Databases: MongoDB, PostgreSQL, Pinecone, ChromDB
Cloud: AWS, Azure
DevOps: Kubernetes, Docker
Languages: Python, SQL, JavaScript
Certifications (Bonus): AWS Professional Solution Architect, AWS Machine
Learning Specialty, Azure Solutions Architect Expert.
What You'll Do:
Collaborate with cross-functional teams to design and build scalable ML
solutions.
Implement state-of-the-art ML techniques, including NLP, Generative AI, RAG,
and Transformer architectures.
Deploy and monitor ML models for high performance and reliability.
Innovate through research, staying ahead of industry trends.
Build scalable data pipelines following best practices.
Present key insights and drive decision-making.
What You Need to Succeed:
Master's degree or equivalent experience in Machine Learning.
5+ years of industry experience in ML, software engineering, and data
engineering.
Proficiency in Python, PyTorch, TensorFlow, and Scikit-learn.
Strong programming skills in Python and JavaScript.
Hands-on experience with ML Ops practices.
Ability to work with research and product teams.
Excellent problem-solving skills and a track record of innovation.
Passion for learning and applying the latest technological advancements.
