Sr. Machine Learning Engineer

• JOB TYPE: Direct Hire/ FTE Position (no agencies/C2C - see notes below)
• LOCATION: Hybrid - Austin, TX
• SALARY RANGE: $300,000 – $350,000/yr
• ESTIMATED DURATION: 40hr/week - Long term
• EXPERIENCE: 5-10 years
• BRAINTRUST JOB ID: 9523

THE OPPORTUNITY

Requirements

Modern Intelligence is seeking an ML Engineer to assist with the creation of classical and hierarchical neural networks for American defense, in areas including sensor fusion, decision making, autonomy, complex inference, electronic warfare, and more.

Modern is using proprietary advances in information and complexity theory to build one AI for defense. Our hierarchical approach provides a dramatic scaling advantage over classical neural networks, naturally enabling very high accuracy on few-shot learning for novel problems, and in many cases, the ability to solve previously-unsolvable problems.

We’re looking for an experienced and insightful ML practitioner who believes that the answer isn’t always just more data, and who has a deep appreciation of the benefits of sparsity, hierarchy, and the mixture-of-experts approach. With theoretical and practical assistance from your team, you’ll help architect solutions to some of the most fundamental problems in machine comprehension, and some of the biggest challenges to the defense industry. You’ll have substantial opportunity for project management and ownership. You’ll work with our contracts team to scope written proposals and project solutions. You’ll work with our R&D platform engineers to help them make their product useful for you and Modern’s scientists. If desired, you’ll have the opportunity to propose new theoretical innovations, and to design experiments to test and refine these innovations. As an early hire, you’ll have the opportunity and active encouragement to grow into leadership and supervisory roles as the company expands.

Interview process:

• Interview with Hiring Manager (45min)
• Take-home assessment (3 hours) + Technical Interview to discuss results (1 hour)
• On-site interview to meet the team (full-day)

Pay Range/Benefits:

• $300k - $350k (all in)
• Relocation package available (within the US)
• Full health, dental, and vision insurance
• Unlimited PTO
• Paid relocation
• Company gym membership
• Free lunch every day

IMPORTANT: This role requires US citizenship due to federal contracting guidelines.

What you’ll be working on

Qualifications

• MS or equivalent experience in Computer Science, Data Science, Mathematics, Statistics, Physics, or related field. PhD or equivalent experience preferred. Candidates still in their graduate program will be considered.
• Strong proficiency in at least one popular ML framework, e.g. Tensorflow or Pytorch. The ideal candidate will have hand-rolled their own ML training environment, even if in a very limited capacity.
• Strong proficiency in coding and data science.
• End-to-end proficiency at the model engineering process -- from data acquisition, storage, processing, and interface design, to model architecting and training, to local or cloud model deployment.
• Proficiency in Probability Theory and other mathematical areas relevant to ML.
• A demonstrable track record of high-quality work in architecting and training neural networks. The ideal candidate will have a publication record demonstrating the ability to make novel contributions.
• Significant experience with computer vision models, natural language models, multimodal data and/or sensor fusion.
• Excellent communication skills, and the ability to work effectively in a team.

If you’re a first-rate engineer, and don’t want to waste your career on incremental advances; if you’re interested in working with an equally brilliant, dedicated, and close-knit team to develop groundbreaking approaches to ML; and if you want to see those approaches turn into real-world products that are orders of magnitude better than anything else on the market; then come work with us.

👉Matcher tips:

• Ensure your resume clearly showcases the skills and qualifications needed for this role.
• Highlight any relevant experience you have gained working in MAA NG companies, early-stage startup or similar environments. These experiences can be particularly valuable.
• Carefully read the job description, paying special attention to the requirement for a generalist skillset. Tailor your application to demonstrate your generalist experience.
• When answering screening questions**, highlight your qualifications listed under the "preferred"** section of the job description. Show how you meet these preferences.
• To set yourself apart from other candidates, refrain from using AI-generated responses. Showcase your unique qualities and experiences instead.
• This is a hybrid role, and be prepared to discuss how your skills and background align with the diverse aspects of the job.
• Note that this role offers a relocation package to candidates who match the qualifications of the position. Be prepared to discuss your willingness and readiness to relocate if applicable.
• IMPORTANT: This role requires US citizenship due to federal contracting guidelines.

Apply Now!