Gatik AI
Machine Learning Engineer
Santa Clara, CA
Sponsorship not specified$170k-$240kDetected 25 days ago
PythonC++Machine LearningPyTorchNLPMLOpsStatisticsSupply ChainLogisticsRoboticsElectrical Engineering
Stay score
odds of building a lasting career here
61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
Level I$152,7971 entry
Level II$187,0752 entries
Level III$221,3743 entries
Level IV$255,6534 entries
$17,075 more — $187,075 — moves this role to Level II and 2 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $187,075 would place this position at wage Level II. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Jose-Sunnyvale-Santa Clara, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Files H-1B transfers
5 transfer filings in the last year, covering 5 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- You will work closely with perception, prediction, planning, infrastructure, systems, and hardware teams to ensure models are efficient, scalable, reliable, and production-ready for both on-vehicle and cloud workflows.
- This role is onsite 5 days a week at our Santa Clara, CA office!
Responsibilities
- End-to-End Model Development: Own the full ML lifecycle, including data strategy, preprocessing, training, evaluation, optimization, deployment, and monitoring.
- Autonomous Driving Models: Develop and improve models supporting perception, prediction, planning, and scene understanding.
- Efficient Neural Network Design: Optimize models using techniques such as quantization, pruning, sparsification, compression, and efficient architecture design to meet strict latency, compute, memory, and power constraints.
- Real-Time Deployment: Integrate trained models into C++-based autonomy systems and optimize inference for production vehicle hardware.
- Model Optimization: Profile and optimize neural networks using CUDA, TensorRT, and related technologies.
- Simulation and Evaluation: Analyze model performance using simulation and real-world driving data, identify failure modes, and drive improvements.
- Scalable ML Infrastructure: Build high-throughput pipelines for training, evaluation, data processing, and large-scale offline inference.
- Data Workflows and Tooling: Develop reliable pipelines for dataset curation, annotation, preprocessing, visualization, diagnostics, benchmarking, and continuous feedback from field data.
- CrossFunctionalIntegration: Partner with autonomy, systems, hardware, and infrastructure teams to ensure ML components integrate reliably into the broader vehicle platform.
Requirements
- Core ML & Systems Expertise:
- Experience deploying and optimizing neural networks for real-time, embedded, robotics, autonomous driving, or other performance-constrained systems.
- Experience with model optimization techniques such as quantization, pruning, compression, and efficient architectures.
- Experience with software architecture, profiling, latency optimization, system-level debugging, and data flow analysis.
- Experience with CUDA and TensorRT is highly desirable.
- Experience with cloud-based ML training and evaluation pipelines, preferably Azure.
Nice to have
- Experience with transformers, multimodal models, diffusion models, world models, or end-to-end driving models is a plus.
- Experience in autonomous driving, robotics, or other safety-critical real-time ML systems is strongly preferred.
- Publications or demonstrated technical contributions in efficient ML, autonomous driving, robotics, or related areas are a plus.
- Prior contributions to large-scale ML systems deployed in production.
- More about Gatik
- We have delivered complete, proprietary AV technology - an integration of software and hardware - to enable earlier successes for our clients in constrained Level 4 autonomy.
- By choosing the middle mile - with defined point-to-point delivery, we have simplified some of the more complex AV challenges, enabling us to achieve full autonomy ahead of competito
- Strong Python skills and experience with frameworks such as PyTorch or TensorFlow.
Compensation
- Salary Range $170,000 - $240,000
Benefits
- Education: MS or PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering, Statistics, Optimization, or a related field.
Company info
- Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion. The company focuses on short-haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world's first fully driverless commercial transportation service with Walmart. Gatik's Class 3-7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation.
- The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom-built to transport freight safely and efficiently between pick-up and drop-off locations on the middle mile. With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all-encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations.
- Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion.
- The company focuses on short-haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world's first fully driverless commercial transportation service with Walmart.
- Gatik's Class 3-7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation.
- The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom-built to transport freight safely and efficiently between pick-up and drop-off locations on the middle mile.
- With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all-encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations.
- What we're looking for
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This listing is sourced directly from Gatik AI's careers page and normalized into a canonical job model.