2303 Machine Design jobs in Passaic, NJ

Bud's Goods

Linden, NJ 07036

Must pass all required background checks
Must have a reliable vehicle
Must be approved by Cannabis Regulatory Commission to work in the cannabis industry
Must be and remain compliant with all legal or company regulations for working in the industry
HS Diploma or 2+ years of related field experience
Experience working with various machines or electrical systems
2+ years of production or manufacturing experience, preferably with 1+ years in cannabis industry
Working knowledge of Metrc
Must be a minimum of 21 years of age
Must have a solid understanding of the cannabis laws, rules and regulations and passion to further understanding and knowledge of the industry, regulations, market trends and competition
Proven track record of managing the scope of operations in a complex and highly regulated business environment
Must posses a valid driver's license
1+ years of experience in a leadership role

JPMorgan Chase &

New York, NY 10025

Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail‑oriented, and motivated by complex analytical problems
Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands‑on experience and solid understanding of machine learning and deep learning methods
PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science or an MS with at least 3 years of industry or research experience in the field.
Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit‑Learn, Pandas)

Spotify USA

New York, NY 10025

Fairygodboss

New York, NY 10025

Genentech

New York, NY 10025

Demonstrated experience with Python and deep learning libraries such as PyTorch, TensorFlow, or JAX
Familiarity with areas of modern machine learning research, such as reinforcement learning, sampling, and multimodal representation learning
Experience designing and building machine learning systems, particularly for molecules and biological sequences
Portfolio of computational projects (available on e.g. GitHub)
Significant education in computer science or the life and physical sciences, or equivalent work experience: for example, anything from a BS+7 to PhD+2 years
Significant education in computer science or the life and physical sciences, or equivalent work experience: for example, anything from a BS+10 to PhD+5 years
Demonstrated research experience, including at least one first author publication or equivalent

Jobot

Paterson, NJ 07501

The Walt Disney Company (Germany) GmbH

New York, NY 10025

Hands‑on experience with cloud‑native data platforms and distributed processing (Snowflake/Databricks/BigQuery/Spark) and orchestration (Airflow/Dagster).
Must have 10+ years of experience in machine learning engineering and/or applied ML roles delivering production ML systems (models + pipelines + monitoring).
Must have 4+ years in a technical leadership capacity, including people leadership and/or strong delivery ownership in ML environment.
Strong proficiency in Python and SQL; software engineering best practices (version control, CI/CD, automated testing).
Must have knowledge of data privacy regulations (GDPR, CCPA) and implementing privacy‑aware data and modeling practices.
Proven experience applying machine learning techniques in code to develop predictive systems at scale (including deep learning where appropriate).