Responsibilities
- Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients.
- Work at the intersection of machine learning, distributed systems, and production software engineering.
- Help transform cutting-edge ML research into robust, production-grade solutions.
- Guide ML architecture decisions and mentor engineers.
- Collaborate with cross-functional teams to deliver high-impact AI solutions across multiple industries.
Requirements
- 8+ years of experience in software engineering, machine learning engineering, or applied AI.
- 3+ years of experience in technical leadership or mentoring engineering teams.
- Strong experience developing and deploying machine learning models in production environments.
- Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or similar.
- Experience designing scalable ML systems and data pipelines.
- Strong programming skills in Python and experience with backend or distributed systems.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Experience with containerization and deployment technologies (Docker, Kubernetes).
- Strong understanding of MLOps practices and model lifecycle management.
- Excellent problem-solving skills and ability to work independently in remote environments.
- Strong written and spoken English communication skills.
- Degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
Nice to Have
- Experience working with LLMs, generative AI systems, or deep learning architectures.
- Experience building ML platforms or internal AI tooling.
- Familiarity with distributed training and large-scale data processing frameworks.
- Experience with feature stores, model monitoring, and ML observability tools.
- Experience delivering ML solutions in client-facing consulting environments.
Benefits
- Competitive compensation with benefits, paid vacation, and sick leave.
- Opportunity to work with a globally diverse team of top engineering talent on the industry’s toughest engineering challenges.
- Ultra-flexible working conditions – generous office equipment allowance for working from home, or a desk at an office/coworking facility near you.
- An enjoyable, start-up work environment, with excellent opportunities for professional growth and development.
- Flexible working hours – remote-first company focused on results, not when or where work is done.
- No business travel necessary.
Work Arrangement
Remote (Worldwide)
Additional Information
- No business travel necessary.
- Flexible working hours.
- Remote-first company.
- Generous office equipment allowance for home office setup.
- Option to use a desk at an office/coworking facility near the candidate.
- Strong written and spoken English communication skills required.
