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Particle Measuring Systems · 3 days ago

Senior Data Scientist – ML Product Development

Niwot, CO

Full-time

Onsite

Senior Level

$150K/yr - $170K/yr

5+ years exp

Particle Measuring Systems is a global leader in micro-contamination monitoring equipment, enhancing the performance of manufacturers in the semiconductor and pharmaceutical industries. They are seeking a Senior Data Scientist to build machine learning solutions that enhance their products and improve user experiences through collaboration with cross-functional teams.

ElectronicsManufacturing

H1B Sponsor Likely

Responsibilities

Design, develop, and deploy machine learning models and algorithms that solve core product challenges (e.g., recommendations, predictions, personalization, automation) with real-time instrumentation

Analyze and interpret large datasets generated by software systems, identifying patterns, anomalies, and behavioral trends

Design, train, and validate Machine Learning models for prediction, classification, clustering, and anomaly detection

Collaborate with cross-functional teams (engineering, product, design) to integrate ML models into production systems

Prototype and experiment with new model architectures and data sources to continuously improve product performance

Monitor and evaluate model performance in production, ensuring robustness, fairness, and scalability

Communicate insights and model results clearly to both technical and non-technical audiences

Contribute to data infrastructure and pipelines that support model training, testing, and deployment

Stay current on advances in machine learning, AI, and data engineering — and help bring new ideas into production

Qualification

Machine LearningPythonData AnalysisCloud-based ML platformsFeature EngineeringStatisticsMLOpsCommunication SkillsCollaboration Skills

Required

Master's or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, or related field (or equivalent experience)

3+ years of experience building and deploying ML models in production environments, with 5-8+ years of relevant experience

Hands-on experience integrating AI models with sensor data, control logic, and signal processing pipelines to improve the accuracy, performance, and predictive capabilities of physical hardware systems

Strong proficiency in Python and popular ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost)

Hands-on experience of data preprocessing, feature engineering, and model evaluation

Solid knowledge of statistics, predictive modeling, and experimental methods

Experience working with cloud-based ML platforms (AWS Sagemaker, GCP Vertex AI, or Azure ML) and containerization (Docker or similar)

Familiarity with software engineering best practices (version control, testing, CI/CD)

Preferred

10+ years experience in production level firmware or software engineering for real-time systems, or equivalent product development experience

Experience developing ML-powered product features (e.g. Predictive maintenance, personalization, recommendations)

Knowledge of A/B testing, experimentation frameworks, and data-driven product iteration

Understanding of MLOps principles and tools for scalable model deployment and monitoring

Excellent communication and collaboration skills; ability to translate complex models into actionable insights

Benefits

Health coverage: medical, dental, vision, fsa, onsite clinic (CO employees), life insurance

401(k) retirement plan with company match

Vacation, holiday, and leave policies

Tuition reimbursement

Employee recognition programs

Employee assistance programs

Company

Particle Measuring Systems

Particle Measuring Systems specializes in viable and nonviable particle counters that measure and monitor contamination levels.

Founded in 1972

Boulder, Colorado, USA

501-1000 employees

https://www.pmeasuring.com/

H1B Sponsorship

Particle Measuring Systems has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Trends of Total Sponsorships

2024 (1)

2022 (1)

2021 (1)