Job description
GenLogs is a transportation-technology company building the next generation of truck intelligence. Through a nationwide network of sensors and proprietary data, we deliver real-time, high-fidelity insights into freight movement for commercial supply-chain customers and public-sector agencies. Our mission is to strengthen America’s logistics backbone, combat freight fraud and cargo theft, and provide near-instantaneous visibility into commercial motor vehicle activity across major freight corridors. By operating at the intersection of edge sensing, computer vision, AI-driven analytics, and large-scale field deployment, GenLogs is transforming how transportation data is captured, secured, and commercialized.
ABOUT THE DATA TEAM
The Data Science team at GenLogs transforms raw observational data from the Trident sensor network into high-value intelligence used by law-enforcement agencies, regulators, ports, and private-sector freight operators. We build models, analytics, and measurement frameworks that enable vehicle detection, entity resolution, behavioral insights, fraud and theft indicators, compliance signals, and network-wide operational performance metrics. Our work sits at the center of the freight intelligence platform, shaping how billions of roadside observations become actionable information. We partner closely with Engineering and Product to deploy algorithms at scale and with Go-to-Market teams to define customer-facing analyses that drive real operational outcomes. The team blends statistical rigor, ML capability, and domain expertise to create a new standard for freight intelligence in the United States.
ABOUT THE JOB
You’re a problem solver at heart. You thrive at the intersection of engineering, math, and machine learning, and you’re motivated by questions that don’t have obvious answers. You bring a background in engineering, computer science, physics, applied math, or another hard science discipline, and you enjoy applying that technical foundation to real-world ML challenges.
You are energized by ambiguity, obsessed with understanding how complex systems behave, and capable of breaking down big problems into tractable iterations. You ask great questions, validate assumptions with data, and are relentless in your pursuit of signal over noise.
WHAT YOU’LL DO
Build machine-learning systems that power some of the most advanced logistics intelligence products in the industry
Analyze large, noisy datasets from cameras, OCR, detections, and geospatial pipelines to uncover actionable patterns
Design and evaluate algorithms for truck re-identification, geospatial clustering, equipment classification, OCR text labeling, anomaly detection, and more
Collaborate with engineering and data engineering teams to scale models from prototype to production
Work closely with product teams to deeply understand customer needs and translate them into modeling and analytics initiatives
Apply scientific thinking to continuously test, iterate, and refine approaches as new data becomes available
REQUIRED QUALIFICATIONS
2–5 years of professional experience in Data Science, Machine Learning, or Software Engineering
Technical foundation in engineering, physics, math, computer science, or related applied fields
Experience deploying or building models using:
Machine learning fundamentals (classification, clustering, time-series, anomaly detection)
Computer vision (OCR, object detection, embeddings)
Geospatial data analysis (mapping, clustering, location intelligence)
Association/sequence pattern mining, feature engineering, or algorithm development
Experience working with cloud-based data tooling (Snowflake, AWS) — not required but nice to have
Strong programming skills in Python and comfort with modern data/ML libraries (PyTorch, Pandas, Scikit-learn, etc.)
Comfort working with real-world messy datasets (sensor data, imagery, telematics, transactional freight data)
WHO WILL SUCCEED HERE
You will love this role if you are:
Relentlessly curious — you ask “why?” repeatedly until you reach the root
Technically fearless — not afraid to dive into large datasets, new ML techniques, or unfamiliar codebases
Impact-driven — you want your models to power real, high-stakes decisions in a massive industry
Comfortable with ambiguity — our data is large, messy, and evolving, and that excites you
Collaborative — you enjoy working with engineers, data teams, and product stakeholders to deliver real customer value
US SALARY RANGE
GenLogs establishes compensation based on role, level, experience, and location. Salary bands are benchmarked against high-growth technology companies and adjusted for market conditions. Equity grants are included in most full-time offers to ensure every team member participates in the company’s long-term value creation. A recruiter will provide a precise range during the hiring process.
BENEFITS
Healthcare (US based only)
Employer-covered comprehensive medical, dental, and vision plans
Employer contribution towards premiums of optional higher-end plans
Time Off
Unlimited PTO
Sick leave
Company holidays (GenLogs observes all US Government holidays)
Flexible leave for caregiving and medical needs
Family Support
Paid parental leave
Professional Development
Budget availability for approved professional development courses, certifications, and training
Travel Support
100% travel reimbursement for all approved company travel and spending
Retirement Savings
401(k) plan (US based employees)
A recruiter can provide more detail about the specific compensation and benefits associated with this role.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.