AI Engineer
Vatic Labs3 months ago
Base Salary
$175k - $275k/yr
Responsibilities
- Design and develop frameworks and tools for foundational-model platforms and trading and research systems.
- Collaborate with researchers and engineers to ensure frameworks work with cloud platforms, machine-learning frameworks and libraries, and modern model architectures.
- Define and run large-scale experiments for rigorous evaluation and in-depth model analysis.
- Support training, evaluation, understanding, and innovation of foundational models.
- Tune and optimize software and algorithms for high performance.
Requirements
- Proven experience with large foundational models and a strong interest in training, evaluation, and model innovation.
- Advanced proficiency in Python development in a Linux environment.
- Strong understanding of machine learning, deep learning, and generative AI methods and technologies.
- Direct experience with multi-GPU model training.
- Demonstrated success building high-performance software.
- Familiarity with parallel computing models and frameworks.
- Strong analytical, problem-solving, communication, and teamwork skills.
- Interest in trading, research, technology, and open-source technologies and prototypes.
Benefits
- Full health insurance coverage for employees and dependents.
- Daily breakfast, lunch, and dinner provided at the office.
- Gym reimbursement and access to an onsite gym.
- Unlimited office snacks.
- Regular team outings, poker, ping pong, and game nights.
- Flat organizational structure with direct executive exposure.
Categories
AI ResearchML Engineering
About Vatic Labs
Vatic Labs is a privately held quantitative trading firm that builds autonomous trading agents and low-latency systems for proprietary trading and market making in electronic markets. Its researchers, engineers, and traders apply machine learning and distributed computing to execute strategies and manage risk. Founded in 2013 and headquartered in New York, the firm trades its own capital and maintains infrastructure that supports high-performance research and execution.