Forward Deployed Engineer – Machine Learning (Northeast U.S.)

Department: Forward Deployed

Location: Boston, New York City, Philadelphia

Compensation: $115,439 – $178,100 • Offers Equity

Employment Type: FullTime

About Gray Swan

Gray Swan protects organizations from emerging AI security threats. We build real-time threat detection, automated validation, and adaptive defenses for AI labs and enterprises. We’re a team of ~25 people, well-funded, and growing fast.

We have strong traction and globally recognized customers, which means employees here take on real responsibility and meaningful equity from day one. This is a high-ownership environment where you’ll work on hard problems, move quickly, and help shape both the product and the company.

Many people join Gray Swan because our mission matters. We’re doing practical, high-impact work in AI safety, that sense of purpose is a core reason why engineers and researchers choose us.

Learn more about how we work.

The Role

As a Forward-Deployed Machine Learning Engineer at Gray Swan AI, you’ll design, build, and deploy AI safety and security solutions directly inside customer environments. You’ll apply state-of-the-art deep learning methods to turn ambiguous, high-stakes problems into production-grade models and systems, rapidly prototyping, iterating, and hardening solutions for real-world use.

If you are an engineer who doesn’t want to stick to just the same workflows, tasks, and stakeholders all the time, this role is probably perfect for you. This role blends applied research, software engineering, and customer delivery, with close collaboration across customers, sales, product, and engineering. You’ll own outcomes end-to-end and operate effectively in fast-moving, customer-facing settings.

What You’ll Do:

• Applied AI/ML:

  • Implement data pipelines, model serving, and evaluation frameworks.

  • Adapt and fine-tune models to domain-specific data and performance requirements.

• Customer-facing delivery:

  • Work with customer teams to understand data constraints, and operational realities.

  • Translate real-world problems into well-scoped proofs-of-concept and deployment architectures.

  • Act as the primary AI/ML technical owner for customer projects, rapidly identifying, scoping, and solving technical issues.

• Rapid Prototyping & Iteration

  • Develop proofs of concept quickly to validate technical feasibility and customer value.

  • Iterate based on user feedback, empirical results, and changing requirements.

  • Balance speed with long-term maintainability.

• Cross-Functional Collaboration

  • Partner with sales, product, research, and platform teams.

  • Communicate findings, tradeoffs, and recommendations.

  • Contribute learnings from deployments back into core product and platform development.

What You Bring:

• Hands-on experience in collaborative environments, working closely with cross-functional teams like data scientists, software engineers, and product managers.

• Demonstrated ability to work independently in ambiguous environments and take full ownership of outcomes.

• Hands-on experience in building and deploying machine learning models and systems.

• Demonstrated expertise in designing, training, and deploying deep learning models with frameworks like PyTorch.

• Demonstrated experience programming in Python and C++.

• Practical experience in developing scalable machine learning pipelines and integrating them with cloud infrastructure (e.g., AWS, GCP, Azure).

• In-depth knowledge of neural network architectures, such as sequence models, transformers, and other state-of-the-art approaches.

• Strong algorithmic problem-solving skills and comprehensive knowledge of ML theory and optimization techniques.

• Proficiency in data preprocessing and transformation, and handling large-scale datasets with multiple modalities.

• Bachelor’s degree in Computer Science, Machine Learning, Engineering, or a related technical field is required.

Bonus Points If You Have:

• A Master’s degree in a relevant technical field, especially with a focus on machine learning and AI safety.

• Experience with AI safety practices, such as model validation, robustness testing, and continuous monitoring for safety and security incidents throughout deployment.

• Familiarity with AI safety and security assessments and adversarial testing.

• Strong collaboration and problem-solving abilities, with an emphasis on driving impactful solutions.

• Experience working with customers, partners, or other external stakeholders to deploy and ensure the success of software products, ideally in a technical pre-sales, technical support, forward-deployed engineering, or similar role.

If you don’t have 100% of these, you should still seriously consider applying. We care more about what you can do than your credentials.

You’ll Thrive Here If You:

• Are looking for a role where you have a huge opportunity to work hard, prove yourself, and build your skillset by trying new things and learning on the job.

• Approach your work proactively and enjoy problem solving

• Can learn fast and are naturally curious

• Are passionate about our mission– to empower the world to use AI safely and securely

What We Offer:

A competitive compensation package designed to reward impact and incentivize growth. Our compensation philosophy is informed by our current valuation and recent industry data.

Salary: $115,439 - $178,100 + a competitive equity package in a startup with real revenue and globally recognized customers

Benefits:

• 401k with up to 4% matching

• 28 days annual leave (vacation + holidays)

• Health, dental, and vision coverage

• Catered lunches (Pittsburgh office)

• Flexible work arrangements

• Visa sponsorship available for exceptional candidates