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Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Lead technical vision and architecture for ML-driven trajectory generation in autonomous vehicles. Build and deploy scalable training pipelines, integrate models into real-time safety-critical onboard systems, mentor senior engineers, drive cross-functional initiatives, and move solutions from research to production using simulation and large-scale datasets.
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Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Customer-facing, hands-on AI builder shaping opportunities, prototyping AI/GenAI solutions, designing end-to-end architectures, leading discovery workshops, supporting RFPs, and enabling implementation handoffs while creating reusable AI assets and accelerators.
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ISEE is seeking a full-time Machine Learning Engineer to join our team. The ideal candidate has several years of work experience.
Role responsibilities include:
- Working on the intersection of sensing and perception algorithms.
- Prototyping and deploying robust computer vision algorithms on ISEE’s vehicle fleet in areas of: Sensor calibration, localization and mapping, fusion, tracking and pattern recognition.
- Benchmarking and maintaining developed modules.
- Work independently to deliver high-quality code in a timely fashion.
- Collaborate with team for testing, evaluation and review of code.
Required Qualifications
- Degree in Computer Science, Electrical Engineering, Robotics or related field.
- Experience in deploying deep learning models at scale on real-world data in at least one of these deep learning frameworks: PyTorch, Tensorflow, Caffe.
- Hands-on experience with developing, training and deploying deep learning models in multimodal (sensors space and temporal) real world data.
- Strong Python and/or C++ skills.
- Passionate about self-driving vehicles and real-world robotic solutions.
- Strong presentation and communication skills.
Preferred
- Publication record in top-tier computer vision or machine learning conferences.
- 3+ yrs industrial experience in deploying Computer Vision/Deep learning algorithms in real-world scenarios.
- Robotics/autonomous experience is a plus.
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
