Senior Machine Learning Engineer

Building and Deploying ML Models

• Design, build, optimize, deploy and monitor machine learning models for production use cases.
• Ensure scalability, reliability, and efficiency of ML pipelines across cloud and on-prem environments.
• Work with data engineers to design data pipelines that feed into ML models.
• Optimize model performance, ensuring low latency and high accuracy.

Leading and Architecting ML Solutions

• Lead a team of ML Engineers, providing technical mentorship and guidance.
• Architect ML solutions that integrate seamlessly with business applications.
• Ensure models are explainable, auditable, and aligned with business goals.
• Drive best practices in MLOps, CI/CD, and model monitoring.

Collaborating and Communicating

• Work closely with business stakeholders to understand problem statements and define ML-driven solutions.
• Collaborate with software engineers, data engineers, platform engineers and product managers to integrate ML models into production systems.
• Present technical concepts to non-technical stakeholders in an easy-to-understand manner.

What We’re Looking For:

Machine Learning Expertise

• Deep understanding of supervised and unsupervised learning, deep learning, and NLP techniques, and large language models (LLMs).
• Experience in training, fine-tuning, and deploying ML and LLM models at scale.
• Proficiency in ML frameworks such as TensorFlow, PyTorch, Scikit-learn etc.

Production and Cloud Deployment

• Hands-on experience deploying models to AWS, GCP, or Azure.
• Understanding of MLOps, including CI/CD for ML models, model monitoring, and retraining pipelines.
• Experience working with Docker, Kubernetes, or serverless architectures is a plus.

Data Handling

• Strong programming skills in Python.
• Proficiency in SQL and working with large-scale datasets.
• Familiarity with distributed computing frameworks like Spark or Dask is a plus.

Leadership and Communication

• Ability to lead and mentor a team of ML Engineers and collaborate effectively across functions.
• Strong communication skills to explain technical concepts to business teams.
• Passion for staying updated with the latest advancements in ML and AI.

Experience Needed:

• 6+ years of experience in machine learning engineering or related roles.
• Experience in deploying and managing ML and LLM models in production.
• Proven track record of working in cross-functional teams and leading ML projects.