Next Step Systems · Remote · US · Machine Learning Engineering $225,000–$275,000 12d ago

Aimlroles; San Francisco (CA); Remote; USD 250,000 - 350,000; Full time

Benefits offered by this job

Medical insurance

Dental

Vision

Savings plan

Job summary

Aimlroles seeks a VP of Research, Machine Learning (ML/AI) to own the research direction and product intelligence for a high-frequency system. This 100% remote role requires shaping how AI reasons, evaluates, and improves in production.

You will drive architecture decisions, evaluation, and guardrails while partnering with product engineering. Expect ownership and a founder-like approach to complex, real-world systems.

Qualifications

• Extensive experience building or evolving ML systems in production.
• Strong AI/ML background with emphasis on long-term behavior and safety.
• Ability to set strategy and evaluate real-world usefulness over benchmarks.

Responsibilities

• Set the research direction for core intelligence, including memory and planning.
• Decide when to design new models vs. adopt external ones.
• Define evaluation frameworks focused on real-world usefulness and safety.
• Own alignment, safety, and guardrail strategy as product concerns.
• Guide frontier techniques and shape early product intelligence direction.

Skills

Production ML systems

AI/ML governance

Evaluation frameworks

Ownership mindset

Decision making under uncertainty

Retrieval-augmented training

Tools

JAX

Python

PyTorch

GPU training/inference

Job description

VP of Research, Machine Learning (ML), Artificial Intelligence (AI) Required, Work From Home

The VP of Research, Machine Learning (ML) will own the research and intelligence direction of this system. The VP of Research, Machine Learning (ML) will define how Artificial Intelligence (AI) reasons, evaluates, and improves in a product used with high frequency. This position is 100% Remote.

MUST BE WILLING TO TAKE A 60 MINUTE CODING ASSESSMENT.

VP of Research, Machine Learning (ML) Responsibilities:

• Set and evolve the research direction for the core intelligence, including context representation, memory, reasoning, planning, and orchestration.
• Decide when to design new model architectures versus adapting or leveraging frontier open-source or commercial models.
• Define evaluation frameworks that measure real-world usefulness, robustness, safety, and long-term behavior, not benchmark vanity.
• Own alignment, safety, and guardrail strategy as first-class product concerns.
• Guide exploration of frontier techniques such as retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, and multimodal systems.
• Shape early product intelligence direction in close partnership with product and application engineering.
• Set the technical bar for research rigor, judgment, and taste across the organization.

VP of Research, Machine Learning (ML) Qualifications:

• Deep experience building or evolving real Machine Learning (ML) systems used in production.
• Artificial Intelligence (AI) experience required.
• Strong technical judgment around model behavior, failure modes, and long-horizon trade-offs.
• A builder's mindset, you care about systems that work in the real world, not just ideas.
• Comfortable making irreversible or high-impact decisions with incomplete information.
• Obsession with evaluation, correctness, and how systems behave over time.
• High ownership mentality; you operate as a founder, not a manager.
• Tech Stack: GPU-based training and inference system, JAX, Python, and PyTorch.

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.