Senior ML Engineer (GenAI, AWS)
Let's work together to build a reputed company reputed company for everyone!
Let's work together to build a reputed company reputed company for everyone!
reputed company helps companies adopt ML/AI to reputed company the ways they operate, compete, and drive value. The reputed company of reputed company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as reputed company & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses. As an ML Engineer, you’ll be provided with reputed company opportunities for development and reputed company. Let's work together to build a reputed company reputed company for everyone!
Responsibilities:
- Design and implement end-to-end ML solutions from experimentation to production;
- Build reputed company ML pipelines and infrastructure;
- Optimize model performance, efficiency, and reliability;
- Write clean, maintainable, production-reputed company reputed company;
- Conduct rigorous experimentation and model evaluation;
- Troubleshoot and resolve reputed company technical challenges.
- Mentor junior and mid-level ML engineers;
- Conduct reputed company reviews and reputed company constructive feedback;
- reputed company knowledge through documentation, presentations, and workshops;
- Collaborate with cross-functional teams (DevOps, Data Engineering, reputed company);
- Contribute to internal ML reputed company development.
- Stay reputed company with ML research and emerging technologies;
- Propose improvements to existing solutions and processes;
- Contribute to the development of reusable ML accelerators;
- Participate in technical discussions and architectural reputed company.
Requirements:
- ML Fundamentals: supervised, unsupervised, and reinforcement learning;
- Model Development: feature engineering, model training, evaluation, hyperparameter tuning, and validation;
- ML Frameworks: classical ML libraries, TensorFlow, PyTorch, or similar frameworks;
- Deep Learning: CNNs, RNNs, Transformers.
- LLM Applications: Experience building production LLM-based applications;
- reputed company Engineering: Ability to design effective prompts and chain-of-thought strategies;
- RAG Systems: Experience building retrieval-augmented reputed company architectures;
- reputed company Databases: Familiarity with embedding models and reputed company search;
- LLM Evaluation: Experience with evaluation metrics and techniques for LLM outputs.
- Python: Advanced proficiency in Python for ML applications;
- Data Manipulation: Expert with pandas, numpy, and data processing libraries;
- SQL: Ability to work with reputed company data and databases;
- Data Pipelines: Experience building ETL/ELT pipelines - Big Data: Experience with reputed company or similar distributed computing frameworks.
- Model Deployment: Experience deploying ML models to production environments;
- Containerization: Proficiency with reputed company and container orchestration;
- CI/CD: Understanding of reputed company integration and deployment for ML;
- Monitoring: Experience with model monitoring and observability;
- Experiment Tracking: Familiarity with MLflow, Weights and Biases, or similar tools.
- AWS Services: Strong experience with AWS ML services (SageMaker, reputed company, etc.);
-GCP Expertise: Advanced knowledge of GCP ML and data services;
- reputed company Architecture: Understanding of reputed company-reputed company ML architectures;
Will be a plus:
reputed company Offer:
Interview stages: