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Phd Machine Learning Startup Jobs in Texas (NOW HIRING)

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field * 5 years of experience in applied machine learning on real use cases * Proficient coding skills and strong software ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization ... grade machine learning systems, spanning model training, tuning, deployment, serving, and ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site +1

$335K - $400K/yr

PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization ... grade machine learning systems, spanning model training, tuning, deployment, serving, and ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization ... grade machine learning systems, spanning model training, tuning, deployment, serving, and ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using ... A PhD is preferred but not necessary. * Experience: * At least 5 years of experience in data ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

bp

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

You will apply machine learning science as a core discipline - developing novel algorithms and ... MSc or PhD degree or equivalent experience in a quantitative field (e.g. Computer Science ...

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Phd Machine Learning Startup information

What are some common challenges faced by PhD-level professionals working in machine learning startups?

PhD-level professionals in machine learning startups often encounter challenges such as balancing research innovation with the need for rapid product development. Unlike academia, startups prioritize practical solutions that fit tight deadlines and resource constraints. Team members typically wear multiple hats and collaborate closely with engineers, product managers, and business stakeholders, requiring strong communication skills and adaptability. Additionally, translating cutting-edge research into scalable, real-world applications can be both intellectually rewarding and demanding.

What do PhD holders in Machine Learning do at startups?

PhD holders in Machine Learning at startups typically lead research and development efforts to create innovative algorithms and models that solve real-world problems. They often work on designing and implementing advanced machine learning solutions, analyzing large datasets, and collaborating with product and engineering teams to bring research ideas to production. Their expertise helps startups stay competitive by driving technological advancements and fostering a culture of innovation.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional in a startup environment, and why are they important?

To excel as a PhD-level Machine Learning professional at a startup, you need advanced expertise in machine learning algorithms, statistical modeling, and a doctoral degree in a related field. Experience with Python, TensorFlow, PyTorch, and version control systems, along with a strong publication record, is typically expected. Initiative, adaptability, and excellent problem-solving and communication abilities are crucial soft skills in the fast-paced startup setting. These competencies enable rapid innovation, effective team collaboration, and successful deployment of machine learning solutions under resource constraints.
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Phd Machine Learning Startup jobs near you

Machine Learning/Deep Learning Engineer(PhD, New Grad)

Bot Auto

Houston, TX • On-site

Full-time

Posted 22 days ago

Job description

Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
Key Responsibilities
  • Model Implementation & Iteration: Participate in the development, training, and optimization of state-of-the-art deep learning models for autonomous driving, with a focus on end-to-end architectures, including object detection, tracking, online mapping, and end-to-end planning.
  • Full Lifecycle Execution: Engage in the entire machine learning workflow under the guidance of domain experts, spanning from data curation and data analysis to model experimentation, hyperparameter tuning, and rigorous performance metric verification.
  • Cross-Functional Collaboration: Partner with simulation, infrastructure, and downstream planning/control teams to deploy, evaluate, and integrate machine learning components into our production pipeline for autonomous trucks.
  • Literature Tracking: Stay abreast of the latest research breakthroughs in computer vision and generative AI, and actively bench-test promising SOTA methods to solve real-world corner cases.
Qualifications
Required:
  • Education: An advanced degree (Master's or Ph.D., including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.
  • Core Knowledge: Strong theoretical foundation in machine learning, deep learning, and computer vision, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs).
  • Technical Stack: Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow, along with strong software engineering fundamentals (data structures, algorithms, and clean coding practices).
  • Attributes: High self-motivation, strong analytical and problem-solving skills, a fast learner in a high-velocity startup environment, and a strong team-player mindset.
Preferred (Targeted Research & Background):
  • Specific Research Directions: Academic thesis or deeply focused research experience in one or more of the following domains:
    • 3D Computer Vision / Bird's-Eye-View (BEV) Perception
    • Online Mapping, Vectorization, or Visual SLAM
    • Prediction and Behavioral Modeling
  • Academic Achievements: A proven track record of research publications in top-tier machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS) as a primary contributor.
  • Engineering Plus: Hands-on experience with model deployment, quantization, distillation, or inference acceleration tools (e.g., TensorRT, ONNX, CUDA, C++).
  • Industry Exposure: Prior internship experience within the autonomous driving industry or advanced robotics labs is highly desirable.

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