Roboflow — Forward Deployed Engineer

Type: Full-time | Remote (US) with ~40–50% travel | Chicago, IL (Midwest strongly preferred) Compensation: $144K–$200K base ($180K–$250K OTE, uncapped variable) + competitive equity Hiring count: 3–5 Visa sponsorship: No — not open to any visas (US citizens / Green Card holders only) Reports to: Nick Herrig, Head of Field Engineering

About Roboflow

Roboflow builds software-as-a-service products that make building with computer vision easy — a "physical AI" company spanning image data management, annotation/labeling, preprocessing, one-click model training, and deployment via API or to the edge. Over 1,000,000 developers use the platform, and it works with 65% of the Fortune 100, primarily in global manufacturing.

Founded: 2019 | Team size: 70 | Total funding: $63.6M (see data conflict — "Why Join" cites $99M+ raised / $77.5M Series B) Industry: AI, Software Development, Devtools Website: roboflow.com Office: Flatiron, NYC (+1 hub)

Why Candidates Should Join

• Real traction at scale: 1M+ developers and 65% of the Fortune 100 are already customers — not a pre-revenue bet.
• Well-capitalized and well-backed: $99M+ raised, $77.5M Series B led by Google Ventures and Y Combinator; investors include Sam Altman and Greg Brockman.
• Strong comp + benefits: $180K–$250K OTE (uncapped variable) plus equity, 100% health insurance for you and family, $4K/yr travel stipend, $350/mo productivity stipend, $350/mo AI tools budget.
• Remote-first across the US: optional NYC/SF hubs with relocation bonus (3x/week hybrid at office locations), flexible async-friendly schedule, co-working stipend.

Intake Call Summary

• Company: Physical AI / computer vision company; works with 65% of the Fortune 100, primarily global manufacturing.
• Role: Hiring FDEs to support strategic customers, drive platform adoption, and accelerate deployment and product development alongside customers.
• Requirements: 2–8 years experience; competencies over strict year counts. Customer-facing experience and execution rigor are critical.
• Comp/logistics: $180K–$250K incl. OTE + equity. Remote with preference for candidates near major cities; relocation bonus available.
• Timeline/urgency: Plan to hire 3–5 FDEs within the next month due to high customer demand and rapid deployment/expansion needs.
• Pain points: Large companies lack internal physical-AI skills, driving high FDE demand; need field insight to support product evolution and adoption.
• Ideal profile: Manufacturing, IoT, or robotics backgrounds with strong software skills; open to solution architect / pre-sales transitions.
• Interview process: Under calibration; technical screening may be added by role.
• Location: Preference for Chicago, Indianapolis, or areas with major airports due to travel needs.
• Visa: Avoiding sponsorship at this stage; may revisit based on pipeline.

HM update (Nick Herrig, Aug 20, 2026): Added a Must-Have — "Highly motivated, coachable, and low-ego — someone who's eager to learn, takes feedback well, and is a team player" — based on initial first-round feedback. Candidates should show excitement for the role, have stories highlighting team skills, and present as coachable.

The Role

Take computer vision deployments from proof-of-concept to production at some of the world's largest manufacturing, logistics, and industrial companies. A hands-on 0-to-1 builder who thrives in ambiguous, real-world environments — embedding with customer teams and shipping production-grade systems that hold up on the factory floor. Roboflow's goal: for "FDE at Roboflow" to carry the resume weight of Palantir or FAANG.

What You'll Be Doing

• Embed with customers (on-site 25–50% of the time) to take validated POCs to first production deployment — the critical 0-to-1 phase.
• Build and configure data pipelines, edge devices, and CV models in real-world physical environments (factories, warehouses, construction sites).
• Serve as Roboflow's eyes and ears in the field — surfacing the gap between what customers say vs. need, feeding insight back to Product and Engineering.
• Write production-grade Python and handle the messy realities of real-world CV: lighting variability, camera calibration, model drift, edge hardware constraints.
• Document deployment architectures, create runbooks, and hand off to Implementation Engineers once the customer runs independently.

Tech stack: Python, Docker, Kubernetes, Linux, NVIDIA Jetson, Computer Vision, ML/MLOps, Edge Computing, Industrial Cameras, Roboflow

Qualifications

Seniority

• 1–8 years of experience in forward deployed, field, solutions architect, or customer-facing software engineering role [Required] (intake call said 2–8 — see conflict)

Work Experience

• Owned a full customer-facing technical deployment end-to-end — from 01 build through customer adoption and post-deployment maintenance [Must have]
• Junior archetype: 1–3 YOE; strong internships (FAANG+) in undergrad; working at a top FDE company, high-growth startup, or customer-facing software engineer [Must have]
• Strong proficiency in Python; experience with systems-level work (Docker, Kubernetes, networking, Linux) [Required]
• Automation, mechanical, or industrial engineers with strong software engineering experience [Required]
• Background in one of Roboflow's target verticals: manufacturing, logistics, automotive, or robotics/automation [Strongly preferred]
• Familiarity with MLOps/CV tooling: model versioning, monitoring, retraining pipelines [Strongly preferred]

Education

• BS in CS, Engineering, or related technical field [Required]

Soft Skills

• Highly motivated, coachable, and low-ego — eager to learn, takes feedback well, team player [Must have]
• Can communicate and build trust with executives, engineers, and floor operators [Must have]

Miscellaneous

• Willing and able to travel 40–50% of the time for on-site customer deployments — Midwest location (Chicago, Indianapolis) strongly preferred given current customer concentration [Required]

Traits to Avoid

• Candidates with only lab/demo/notebook ML experience — no real-world, physical-environment production deployments
• Purely research-oriented or pre-sales-only engineers with no hands-on build and deployment track record

Role Details

• Salary | $144K–$200K base ($180K–$250K OTE, uncapped variable)
• Equity | Competitive equity
• On-site policy | Remote (US, US daytime hours); ~40–50% travel for on-site deployments
• Visa sponsorship | Not open to any visas (US citizens / Green Card holders only)
• Employment type | Full-time
• Location | Chicago, IL; Indianapolis, IN; Cleveland, OH; Midwest (Remote); NYC/SF/DC hubs

Screening Questions

1. What's the one thing you've built that you are most proud of?
2. Tell me about a time you received difficult feedback at work. What did you do with it?
3. Tell me about a customer or coworker that you butted heads with. How did you resolve your differences?
4. What is your salary expectation?
5. How actively are you exploring new opportunities?

Interview Process

Stage 1 — Submit candidate After submitting, you'll be notified if the hiring manager wants to proceed.

Stage 2 — Info Chat / Introduction with Hiring Manager (30 min) (description says 45 min — see conflict) Conversation with a member of the FDE/IE team (or Nick Herrig). Assesses overall mindset and skillset, focused on drive and follow-through, coachability and collaboration, and communication and customer instinct.

Stage 3 — First Round: Technical Deep Dive (60 min) Conducted by an FDE/IE team member. Evaluates zero-to-one and tinkerer authenticity (real deployment ownership, personal hardware projects, self-directed builds) and field resilience (adapting when hardware, access, or scope doesn't match expectations). Includes a live coding or architecture session on Python, systems-level work, and production deployment.

Stage 4 — Technical Challenge / Demo (30 min) Candidate builds a project with Roboflow and presents. Panel includes info-chat and first-round interviewers plus one additional team member (e.g., Dom, Alexei, Dave). Evaluators watch presentation, build scoping, and responsiveness to feedback. Candidates may be asked to submit a two-minute Loom by end of day. References run in parallel by Nick.

Stage 5 — GTM Final: Culture & Leadership (45 min) Two 30-min conversations with Josh, Pete, or Joseph Nelson (CEO). Sells the candidate on the role, confirms motivation and cultural fit, and assesses alignment with Roboflow's mission and values.

Stage 6 — Offer Extended

Stage 7 — Candidate Hired

Ideal Companies & Backgrounds

Updated Aug 20, 2026

Forward Deployed / Field Engineering powerhouses Databricks, OpenAI, Anthropic, Snowflake, Scale AI, Rippling, Ramp, Anduril Industries, Datadog, HashiCorp, MongoDB

Big Tech companies with customer-facing SWE roles Amazon Web Services (AWS), NVIDIA, Samsara, Amazon, Meta, Netflix, Google

Industrial automation & IoT platform companies (with strong SWE talent) Rockwell Automation, Siemens Digital Industries Software, Honeywell, Abbott, PTC, AVEVA, FANUC America, Cognex, KEYENCE

Robotics & autonomous systems companies (hardware + software integration) Boston Dynamics, Locus Robotics, 6 River Systems, Nuro, Waymo, Aurora, Symbotic, Covariant, Dexterity, Realtime Robotics

Ideal Candidate Profiles

None provided in the role materials.

Rejected Candidate Feedback

• Customer-facing industrial deployments: Must clearly demonstrate on-site experience in factories or similar physical environments, not just lab/demo work.
• Production SWE track record: Prioritize proven end-to-end build and deployment in real-world settings over test, research, or support roles.
• Coachability and team interaction: Candidates must share concrete examples of handling feedback and collaborating with diverse customer and engineering teams.
• Tenure / recency (HM Review): One candidate rejected for short tenures and lack of recent SWE experience — watch job-hopping and stale hands-on coding.