Junior Machine Learning Developer
Somerville, Morocco · На постоянной основе
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- Опубликовано
- 3 часа назад
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About Laminar
Laminar, formerly known as H2Ok Innovations, is at the forefront of cleantech advancement, revolutionizing process industries and manufacturing with a focus on operational efficiency and sustainability. Utilizing Laminar AI Co-pilot models alongside innovative sensor technology, the company enhances facility performance across sectors such as process manufacturing, water management, energy conservation, and waste reduction. Based in Greentown Labs, a leading cleantech innovation hub, this woman-founded startup is backed by prestigious investors and has earned recognition along with adoption from major global corporations including Unilever and The Coca-Cola Company.
Role Overview
As a Junior Machine Learning Developer, you will play a pivotal role in developing and refining the machine learning models central to Laminar’s process optimization technologies. You will collaborate closely with a team of ML/Data Scientists to transition models from prototypes to production-ready systems. Your contributions will support a range of industrial processes such as clean-in-place (CIP), product changeovers, and material identification, among others.
Key Responsibilities
- Create cutting-edge machine learning models utilizing Laminar's proprietary spectral sensors and software platform to drive new standards in fluid-based industrial processes.
- Design and execute experiments to assess model generalizability, accuracy, and robustness against process variability.
- Develop data preprocessing and feature extraction pipelines to interpret diverse, multi-modal sensor data from real-world operations.
- Maintain model reliability through monitoring and correcting for model drift, sensor drift, and process anomalies.
- Collaborate with ML Scientists and software engineers to build effective machine learning infrastructure and tooling.
- Engage in diverse modeling tasks including chemometrics, hybrid modeling, self-supervised learning, distribution modeling, drift/anomaly detection, similarity analyses, and continuous calibration.
Candidate Profile
Required Qualifications:
- Proficiency in at least one Python-based ML framework such as PyTorch, JAX, or TensorFlow.
- Strong knowledge of Python numerical and data libraries including NumPy, Polars, Pandas, and scikit-learn.
- Ability to produce clean, maintainable, and well-tested code while meeting project deadlines.
- Self-motivated with capability to execute technical objectives independently and deliver results.
- Detail-oriented with a natural curiosity towards data analysis and a proactive approach to testing hypotheses and refining models.
Preferred Experience:
- Background in chemical engineering, process engineering, or manufacturing domains.
- Familiarity with cloud platforms such as AWS or GCP and experience with Databricks.
- Experience working with spectral data, time-series models, or sensor-based machine learning.
- Knowledge of Bayesian modeling and probabilistic inference techniques.
- Exposure to building real-world products incorporating machine learning and user-focused design principles.
Benefits and Culture
- Opportunity to significantly impact both product development and company culture.
- Comprehensive benefits including medical, dental, vision, life insurance, disability coverage, transportation benefit, and wellness programs.
- 401(k) with employer match and equity participation in a rapidly growing startup.
- Competitive salary and potential bonus incentives.
- Dynamic, inclusive, and empowering work environment encouraging creativity and excellence.
- Access to Greentown Labs’ extensive cleantech community network.
- Pathways for professional growth and development.
Additional Information
Laminar prioritizes diversity and inclusion, encouraging applications from women and nonbinary individuals, and fosters a supportive environment for extraordinary growth and innovation. The recruitment process includes multiple interview stages with opportunities for skills assessments and final interviews with company founders. The company uses AI-enhanced tools to assist with the hiring process but maintains human-led final decisions. Laminar offers an impressive benefits package for its stage and commits to covering 100% of individual premiums for HMO medical plans, vision, and dental. Other perks include flexible paid time off, holidays, transportation and health & wellness stipends, and membership at Greentown Labs. Background checks and references are part of the final hiring steps.