Machine Learning Engineer

Unitxlabs
HQ, HQ

Who this role is best for

Best suited to mid-level machine learning engineers with expertise in computer vision and real-time inference optimization working in industrial automation.

Best fit for

  • Candidates with experience in deploying ML models in industrial settings.
    — “deployed 1,000+ mission-critical systems across 190+ of the world's leading manufacturers' production lines
  • Engineers skilled in advanced computer vision techniques and real-time inference.
    — “implement advanced computer vision techniques to ensure pixel-level precision and real-time inference
  • Developers comfortable with both edge and cloud-based ML deployments.
    — “Develop scalable ML pipelines for deployment on both edge devices and cloud-based systems

Things to consider

  • Role requires maintaining 24/7 fault tolerance in manufacturing environments.
    — “ensure 24/7 fault tolerance in a manufacturing environment
  • Must optimize models for sub-20 millisecond processing times.
    — “ensuring processing times remain under 20 milliseconds

How to stand out

  • Highlight specific instances where you improved model precision in production.
    — “ensure pixel-level precision and real-time inference
  • Demonstrate experience with transformer-based architectures and SAM.
    — “including Stable Diffusion, Segment Anything Model (SAM), and transformer-based architectures
  • Showcase contributions to academic publications or open-source projects.
    — “contribute to academic publications, patents, and open-source projects
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · CompanyLevel · Mid Level

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • develop and optimize machine learning models for defect detection and segmentation
Typical background
Bachelor's degree in Computer Science, Mathematics, Statistics

Skills & requirements

Required

Deep LearningNeural NetworksMachine Learning Pipeline DevelopmentSensor FusionComputer VisionReal-time Inference OptimizationStatistical ModelingA/B Testing

Preferred

Self-supervised LearningDomain AdaptationMultimodal Data FusionReinforcement LearningGenerative AI

Stack & domain

Deep LearningNeural NetworksMachine Learning Pipeline DevelopmentSensor FusionSignal ProcessingComputer VisionReal-time Inference OptimizationStatistical ModelingA/b TestingCollaborationProblem-solvingAttention To DetailAIManufacturingQuality Assurance

About the role

Original posting from Unitxlabs via Ashby

Job Title:

Machine Learning Engineer

About Us:

UnitX builds the world's leading physical AI systems to automate repetitive visual tasks in factories. UnitX is a fast-moving startup with a team from Stanford, MIT, Google, and beyond. Since inception, UnitX has deployed 1,000+ mission-critical systems across 190+ of the world's leading manufacturers' production lines. Every year, $15B worth of products go through UnitX's AI inspection system to ensure quality.

Join us for the rare opportunity to work on computer-vision-driven products that go beyond the state of the art and that improve global manufacturing efficiency.

What You'll Do:

  • Develop & Optimize Machine Learning Models: Design, train, and optimize deep learning models for defect detection and segmentation using high-resolution images and 3D sensor inputs. You will implement advanced computer vision techniques (including Stable Diffusion, Segment Anything Model (SAM), and transformer-based architectures) to ensure pixel-level precision and real-time inference.
  • Build Automated Pipelines: Develop and maintain automated pipelines for data preprocessing, augmentation, and model training to continuously optimize deployed solutions.
  • Deploy & Maintain Production-Ready Software: Develop scalable ML pipelines for deployment on both edge devices and cloud-based systems. You will optimize model inference for real-time decision-making, ensuring processing times remain under 20 milliseconds.
  • Collaborate Cross-Functionally: Work closely with software engineers, robotics specialists, and hardware teams to seamlessly integrate ML solutions into fully automated industrial workflows.
  • Monitor & Ensure Reliability: Implement automated monitoring and alerting systems to track model drift, identify failures, and ensure 24/7 fault tolerance in a manufacturing environment.
  • Develop Evaluation & Interpretability Tools: Create frameworks to assess model accuracy, precision, recall, and efficiency. You will design visualization dashboards, conduct A/B testing, and leverage explainable AI (XAI) to improve transparency in quality assurance.
  • Drive R&D & Cutting-Edge Solutions: Investigate emerging AI/CV techniques, including self-supervised learning, domain adaptation, and multimodal data fusion. You will develop novel architectures incorporating reinforcement learning and Generative AI, and contribute to academic publications, patents, and open-source projects.

Who You Are:

  • Education: Bachelor's degree (or foreign equivalent) in Computer Science, Mathematics, Statistics, or a closely related discipline.
  • Experience: 3+ years of experience in the job offered or a related occupation.
  • Technical Expertise: Must possess at least 3 years of hands-on experience in the following areas:
  • Deep Learning & Neural Networks
  • Machine Learning Pipeline Development
  • Sensor Fusion & Signal Processing
  • Computer Vision & Real-Time Inference Optimization
  • Statistical Modeling & A/B Testing

Compensation & Benefits

  • Salary Range: $174,304 – $200,000 per year. (Final compensation is based on experience).
  • Full Medical, Dental, Vision, 401k
  • Unlimited PTO
  • Daily meals provided

HOW TO APPLY

Please send your resume and a cover letter to james@unitxlabs.com and ensure you include Ref#MM0426 in the subject line.

Source: Unitxlabs careers (Ashby)

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