Technical Lead, Machine Learning
Accountabilities Design, build, and scale production machine learning systems supporting advanced AI-powered applications.
Own the infrastructure and execution layer required to train, deploy, monitor, and optimize large language models in production environments.
Develop and maintain training pipelines, evaluation frameworks, and data workflows to continuously improve model performance.
Fine-tune foundation models using modern techniques such as LoRA, QLoRA, supervised fine-tuning (SFT), and direct preference optimization (DPO).
Optimize model inference performance, latency, reliability, and GPU resource utilization.
Build high-quality datasets and establish robust evaluation processes to measure and improve AI system capabilities.
Manage deployment workflows, monitoring, observability, and reliability of machine learning services.
Define engineering standards, contribute to technical strategy, and promote best practices across the ML engineering function.
Mentor and support a high-performing machine learning team while fostering a culture of ownership and technical excellence.
Collaborate closely with backend engineers, product teams, and other stakeholders to translate AI capabilities into impactful user experiences.
Requirements
Proven experience building and deploying production machine learning systems used by real users.
Strong programming skills in Python with hands-on experience using machine learning frameworks such as PyTorch or JAX.
Practical experience with large language models, including fine-tuning, evaluation, and inference optimization.
Deep understanding of machine learning infrastructure, distributed training, and GPU-based computing environments.
Strong software engineering mindset with a focus on scalability, reliability, maintainability, and high-quality code.
Experience designing ML pipelines, deployment workflows, monitoring systems, and production AI services.
Ability to take ownership of complex technical challenges and operate effectively in a fast-paced startup environment.
Strong communication and collaboration skills with the ability to influence technical decisions and mentor other engineers.
Experience leading or guiding machine learning teams is highly desirable.
Benefits
Founding engineering role with significant ownership over technical direction and product architecture.
Opportunity to build AI infrastructure and systems from the earliest stages of development.
Competitive compensation package including cash compensation and equity opportunities.
Remote-first working environment with flexibility across eligible locations.
Opportunity to work with a small, highly talented engineering team solving challenging AI problems.
Strong impact and visibility, with the ability to shape engineering culture and standards.
Long-term growth opportunities within an ambitious AI-focused environment.
Exposure to cutting-edge technologies across large language models, machine learning infrastructure, and AI product development.
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?
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