Roboflow — Forward Deployed Engineer

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