
Pibit.AI-Machine Learning Engineer
2 weeks ago
Job Title: Machine Learning Engineer
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.
● 2+ 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.
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