Lead Machine Learning

Role Overview

We are seeking a Lead Machine Learning to spearhead our ML initiatives, manage a team of data scientists, and ensure the successful delivery of AI-driven solutions. You will be responsible for leading research, development, and deployment of deep learning models while ensuring alignment with business objectives. As a team lead, you will oversee deliverables, conduct 1-on-1 meetings, and provide mentorship to junior team members.

Key Responsibilities

• Technical Leadership & Model Development

  • Lead the design, development, and fine-tuning of deep learning models (e.g., transformers, LLMs, multimodal models).
  • Ensure models remain relevant and scalable as data evolves and new markets emerge.
  • Collaborate with data engineers, ML engineers, and backend developers to ensure optimal performance and deployment.

• Project & Deliverables Management

  • Define project timelines, milestones, and deliverables in alignment with business goals.
  • Track progress, ensure deadlines are met, and mitigate risks.
  • Regularly report updates to key stakeholders.

• Team Leadership & People Management

  • Conduct 1-on-1 meetings with team members to provide feedback, address concerns, and support professional growth.
  • Foster a collaborative and high-performing work culture.
  • Provide technical guidance and mentorship to junior data scientists.

• Data Strategy & Process Optimization

  • Oversee data collection, cleaning, and preprocessing strategies for optimal model training.
  • Identify opportunities to improve existing ML pipelines and processes.
  • Stay up to date with the latest advancements in ML and AI, ensuring best practices are adopted.

Required Skills & Qualifications

• Strong expertise in PyTorch and ML libraries (e.g., Hugging Face, PyTorch Lightning, Scikit-learn).
• Deep understanding of transformers, LLMs, and deep learning architectures (e.g., ViT, BeiT, GPT).
• Proven ability to lead ML projects from research to deployment.
• Strong Python & SQL programming skills.
• Experience managing deliverables, setting timelines, and leading teams.
• Note: Experience with automated ML solutions (e.g., GCP AutoML, Azure AutoML) does not qualify as ML experience.

Preferred Skills

• Experience with cloud computing platforms (AWS, GCP, Azure).
• Knowledge of distributed LLM training optimization (e.g., DeepSpeed, QAT, model parallelization).
• Familiarity with cloud-based training solutions (e.g., Vertex AI, SageMaker).
• Prior experience managing or mentoring a team.

Why Join Us?

• Opportunity to lead a team working on cutting-edge AI and ML models.
• A culture that values innovation, mentorship, and technical excellence.
• Career growth in a fast-paced, high-impact environment.

If you are a results-driven data science leader with a passion for AI and team development, we encourage you to apply!