Junior Machine Learning Developer
Somerville, Morocco · पूर्णवेळ
अर्ज करणारे पहिले व्हा
- अनुभव
- कोणतेही
- पगार
- —
- रिक्त जागा
- 1
- पोस्ट केले
- ८ तासांपूर्वी
- कार्य मोड
- कार्यालयात
- सारांश
- अर्ज करणे आवश्यक आहे
तुम्ही जिथे काम कराल
नोकरीचे वर्णन
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.