Machine Learning Engineer

Title: Machine Learning engineer

Location: Remote

Hiring Mode: Only W2

Roles & Responsibilities

·   Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals.

·   Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment.

·   Collaborate with Research, Product, and Infrastructure teams to define goals, milestones, and success metrics.

·   Provide technical direction on large-scale model training, fine-tuning, and distributed systems design.

·   Implement best practices in MLOps, model governance, experiment tracking, and CI/CD for ML.

·   Manage compute resources, budgets, and ensure compliance with data security and responsible AI standards.

·   Communicate progress, risks, and results to stakeholders and executives effectively.

·   Overlap of 6 hours with PST time zone is mandatory.

Required Skills & Qualifications

·   9+ yrs of strong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs).

·   Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed

·   Hands-on experience in Docker for Production deployment. 

·   Proven experience managing teams delivering ML/LLM models in production environments.

·   Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, Google Cloud Platform, Azure).

·   Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines.

·   Excellent leadership, communication, and cross-functional collaboration skills.

·   Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD preferred).

Nice to Have 

·   Experience building Agentic applications 

·   Experience training or fine-tuning foundation models.

·   Contributions to open-source ML or LLM frameworks.

·   Understanding of Responsible AI, bias mitigation, and model interpretability.