Staff Machine Learning Engineer, Technical Lead

Paperless Parts; Boston (MA); On-site; USD 195,000 - 263,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Unlimited PTO

13+ paid holidays

Wellness stipend

401(k) plan

Job summary

Paperless Parts in Boston, MA is seeking a Staff Machine Learning Engineer, Technical Lead to head a new ML pod and translate cutting-edge models into scalable training pipelines and inference services.

You will mentor early-career ML engineers, drive end-to-end ML lifecycle from data labeling to deployment, and collaborate with researchers and product teams to deliver high‑impact AI solutions for aerospace, defense, and medical devices.

Qualifications

• 8+ years in R&D roles with SaaS at scale
• Strong foundation in ML/AI fundamentals and math behind AI
• Ability to communicate complex concepts to non-technical stakeholders

Responsibilities

• Own planning and execution of the AI/ML pod backlog
• Prototype and transition proofs‑of‑concept to production services
• Operationalize ML infrastructure for scalable data labeling and deployment
• Define benchmarks and track metrics to guide tech decisions
• Mentor early-career ML engineers and foster rigorous engineering culture

Skills

ML theory

MLOps

Mentoring

Education

Computer Science or Applied Mathematics degree

Tools

AWS SageMaker

Job description

Staff Machine Learning Engineer, Technical Lead

Paperless Parts is a SaaS startup helping manufacturers quote faster and win more work. From rockets to medical devices, we power the parts that move the world forward.

This position requires activities that are subject to US Export Control Laws and require US Citizenship or Green Card holder.

About the Role

Step into the role of Technical Lead for our newly formed engineering pod, building the core manufacturing intelligence engine powering the future of Paperless Parts. In this high-leverage role, you will act as the bridge between the art of the possible and high-velocity engineering execution. You will translate cutting-edge models and algorithms into production-grade training pipelines and inference services.

As the technical anchor of a lean, ambitious team, you will drive R&D execution across our entire machine learning lifecycle—from data labeling strategies to low-latency model inference. You will ensure that our approach to computer vision, document intelligence, and predictive modeling is both mathematically rigorous and operationally sound.

Who You Are

• Rigorous yet Pragmatic: You possess a deep theoretical grounding in machine learning and artificial intelligence fundamentals, but you are driven by shipping code that solves real-world, industrial problems. You don’t just apply models; you understand the underlying mathematics, optimization functions, and architectural trade-offs.
• Mentor & Force Multiplier: You are passionate about teaching and elevating early-career technical talent. You enjoy breaking down complex concepts and foster a culture of engineering discipline and curiosity.
• AI Strategist: You understand the trade-offs inherent in technology decisions and think strategically about when to use frontier models, when to train our own, and when to use deterministic solutions.
• Collaborative Partner: You seamlessly collaborate with researchers, other engineering teams, and business stakeholders, helping ensure we build the right technology, deploy it scalably, and bring it to market.

Why You'll Love Working Here

• R&D Ownership: You will lead the technical execution of a new, highly visible engineering pod tasked with solving some of the toughest geometric and document-processing challenges in tech.
• Complex Data & Unique Problems: Our engineering team deals with rich data, including 2D drawings and 3D CAD models. Your work will change what’s possible in manufacturing.
• A Culture of Rigor and Velocity: We value intentionality, persistence, and deep technical discipline. You will have the freedom to meld academic-level inquiry with the agility of a fast-scaling startup.
• High-Impact Mission: Our platform powers manufacturing for critical industries like aerospace, defense, and medical devices. The models your team deploys directly impact the physical creation of products that move the world forward.

What You'll Do

• Drive R&D Execution: Own planning and execution of the AI/ML pod’s backlog. Partner closely with the Chief Scientist and other engineering pods to ensure the research pipeline aligns smoothly with border product timelines.
• Prototype and Transition: Lead the hands‑on prototyping of novel solutions and transition of successful proofs‑of‑concept into production‑ready services. Guide the strategic migration of workloads, identifying opportunities to shift repetitive tasks from expensive frontier models to fine‑tuned, open‑source architectures.
• Operationalize ML Infrastructure: Develop scalable, repeatable approaches to labeling data, training models, and deploying services that support our products with AI capabilities.
• Design Rigorous Benchmarks: Define and track metrics that evaluate the effectiveness and costs of our AI‑powered solutions, enabling key technology decisions to be data‑driven.
• Mentor the Pod: Act as the technical anchor and primary mentor for early‑career ML engineers. Cultivate an engineering culture of deep theoretical and practical rigor through hands‑on pairing and comprehensive design and code reviews.

What You'll Bring

• 8+ years of experience in relevant R&D roles with a strong background in SaaS products at scale (start‑up to scale‑up transition experience preferred).
• Advanced Academic Foundation: a technical degree in Computer Science, Applied Mathematics, or closely related field, with a strong understanding of the mathematics behind modern AI/ML techniques is essential. An advanced degree and track record of peer‑reviewed publications is a strong plus when paired with proven software experience in industry.
• AI/ML Fundamentals: A robust understanding of core machine learning and deep learning theory, including neural networks, statistical modeling and inference, and metric learning.
• MLOps: Experience working with cloud‑native patterns for ML pipelines, including platforms like AWS SageMaker.
• Communication Mastery: Exceptional ability to communicate complex technical concepts to non‑technical stakeholders and influence decisions without relying on authority. This may include technical talks and publications.

Why Join Us?

• Impactful Work: Your contributions will power industries critical to our society and economy, making a real difference.
• Continuous Learning: We invest in our people and offer opportunities to learn, grow, and advance their careers.
• Supportive Culture: Our team is our greatest asset, and we foster an environment where everyone can thrive.

If you’re a forward‑thinking engineer eager to make a significant impact while working with a talented, driven team, we’d love to hear from you!

Salary range: $195,000 - $263,000

The job posting range is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee’s pay position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, performance, sales or revenue‑based metrics, and business or organizational needs.

Paperless Parts Life

Culture: At Paperless Parts, we value intentionality, persistence and relationships. We live and breathe these values every day. As a fast‑growing company, we’re continually improving what we’ve built while still building from the ground up.

Boston Office: Our office is full of energy; people regularly collaborate to solve complex problems. We recognize that people work well in different environments and have intentionally designed our office to provide collaborative spaces and quiet focus areas. Our height‑adjustable desks are set up with additional monitors, and employees are provided with the latest Apple technology to support productivity. Our headquarters is located in downtown Boston, MA and easily accessible to most transit routes (Red/Blue/Orange/Green Line/South Station/North Station).

Encinitas Office: Our California office is our newest office which seats our West Coast sales team. The office has an open floor plan with several conference rooms to encourage collaboration with your colleagues in California and TV's to connect with those sitting in Boston or remotely. The office is walking distance from Downtown Encinitas, the Coaster train stop, and tons of activities on the 101.

Benefits:

• 100% coverage of health, dental, and vision for you and your dependent
• Competitive compensation philosophy
• Unlimited PTO
• 13+ paid holidays
• Company‑sponsored wellness stipend
• Pre‑tax Commuter and FSA/Dependent Care FSA
• 401(k) plan
• Employee recognition program

Responsible for adherence to all security and privacy requirements, rules and regulations and implement as required.

Paperless Parts is committed to cultivating an equitable, inclusive, and supportive environment for all employees. We believe this environment creates a safe space for employees to share their experiences, brainstorm ideas, and grow their careers. Paperless Parts is an Equal Opportunity & affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.