Machine Learning Team Lead

Machine Learning Team Lead

About Us

At Convergence, we're transforming the way AI integrates into our daily lives. Our team is developing the next generation of AI agents that don't just process information but take actions, learn from experience, and collaborate with humans. By introducing Large Meta Learning Models (LMLMs) that integrate memory as a core component, we're enabling AI to improve continuously through user feedback and acquire new skills during real-time use.

We believe in freeing individuals and businesses from mundane, repetitive tasks, allowing them to focus on innovative and creative work that truly matters. Proxy, our personalised AI assistants collaborate with users to enhance productivity and creativity. With a recent $12 million pre-seed funding from Balderton Capital, Salesforce Ventures, and Shopify Ventures, we're poised to make a significant impact in the AI space.

The Role

We are looking for a technical Team Lead to guide our ML engineering team building Proxy, our generalist agent. You will lead a small, talented team equipped with substantial GPU resources, focusing on training multi-modal vision VLMs and action models.

As Team Lead, you'll be responsible for both technical leadership and team management, helping establish the foundations of machine learning engineering at Convergence while mentoring and growing your team.

ResponsibilitiesTeam Leadership

• Lead and mentor a team of ML engineers and researchers

• Define technical roadmap and priorities for model development

• Foster a culture of experimentation and continuous learning

• Collaborate with engineering teams to integrate models into production

• Guide career development and growth for team members

Technical Direction

• Oversee implementation and testing of fine-tuning and preference learning techniques like DPO

• Guide development of data collection strategies, including synthetic data pipelines and annotation workflows

• Lead architectural decisions for model training and deployment

• Define best practices for ML workflows and experimentation

Day-to-Day Activities

• Review and guide experimental design and implementation

• Lead team planning and technical discussions

• Hands-on involvement in critical technical decisions

• Oversee end-to-end experiment ownership by team members

• Guide improvements in:

  • Data quality and pipeline efficiency

  • Model training and evaluation workflows

  • Infrastructure for model inference

  • Integration with the broader Proxy system

Requirements

• Strong technical background in ML engineering with 5+ years experience

• Direct experience training VLMs using methods like distillation and fine-tuning

• Experience with large-scale distributed training and inference

• Track record of leading technical teams or projects

• Proficiency in PyTorch and ML infrastructure

• Strong software engineering foundations

• Experience mentoring and developing engineers

Bonus Qualifications

• Experience training Llama models or other open source models

• Background in fine-tuning frameworks and RLHF

• Experience with ML ops and improving ML practices

• Track record of building high-performing technical teams

• Experience working in fast-paced startup environments

Why Join Us?

• Lead a talented team at the cutting edge of AI

• Shape the technical direction of a well-funded AI startup

• Work on challenging problems that impact users' daily lives

• Collaborative and innovative work environment

• Significant autonomy in technical and team decisions

• Competitive compensation package including equity

• Professional development opportunities