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Engineer II, Data Engineering
2 months ago
HARMAN’s engineers and designers are creative, purposeful and agile. As part of this team, you’ll combine your technical expertise with innovative ideas to help drive cutting-edge solutions in the car, enterprise and connected ecosystem. Every day, you will push the boundaries of creative design, and HARMAN is committed to providing you with the opportunities, innovative technologies and resources to build a successful career.
A Career at HARMAN
As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you’ll discover that at HARMAN you can grow, make a difference and be proud of the work you do everyday.
About the Role
We are currently seeking a Data Engineer focused on Machine Learning ML, with working experience and knowledge in data-based ML, to support our AI Lab teams for Harman products. This position requires professional knowledge and/or experience in the machine learning life cycle from data/feature engineering to deployment to improvement), to support development and improvement of Harman products. This role is responsible for developing MLOps, and ML pipelines for ML models, with (1) competency to develop and solve ML use cases efficiently with reasonable SW engineering quality; (2) strong problem solving, ML and coding skills. Specific ML models are developed or optimized by using big and various datasets from Harman databases and data lakes (Azure, DataBricks, etc.), and by using all available tools and software. The ML models are deployed and maintained in vehicles and the cloud for Harman OEMs and vehicles.
What You Will Do
What You Need
Bachelor or master’s degree in Computer Science, CE, EE, or any equivalent degree, 5+ years of experience. Minimum 5+ years of overall experience working in data analytics and ML, supervised / unsupervised learning, reinforcement learning, deep learning or LLMs or Gen AI for industrial applications. 3+ years of experience with Cloud (Azure, AWS, etc.) or Databricks MLOPs/Labs, ML Studio, PyTorch / TensorFlow, SKlearn, or LangChain, etc. 3+ years of working experience with software tools: PySpark, Python (Jupyter, Colab, or PyCharm, etc.), SQL, scripting, AWS (Athena, EC2, S3, etc.), Linux, Android or Embedded Systems (ECUs, etc.) 3+ years of professional experience with ML engineering, model training, testing, deployment, and improvement in a production environment. Create impactful demonstrations to showcase problem-solving solutions, develop and solve ML use cases efficiently. Contribute to cross-functional technical discussions/collaborations and drive the adoption of best practices. Contribute to strategy, task execution, and documentation of knowledge discovered and transferred, customers/projects stories.What is Nice to Have
Knowledge of LLMs (GPT-4, LlaMA 2, RAG, LangChain, etc.). Providing domain-specific ML algorithms for log analysis, prediction or optimization. Experience in testing and improving software or firmware in the automotive industry.What Makes You Eligible
You will be required to attend the Harman local office at least once a week Successfully complete a background investigation and drug screen as a condition of employmentWhat We Offer
Access to employee discounts on world-class Harman and Samsung products (JBL, HARMAN Kardon, AKG, etc.) HARMAN Flex, our new flexible workplace program will allow employees to continue to build a culture of trust, autonomy, and success by working remotely Extensive training opportunities through our own HARMAN University Competitive wellness benefits Tuition Reimbursement Access to HARMAN Campus Fitness Center and Cafeteria An inclusive and diverse work environment that fosters and encourages professional and personal developmentHARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard torace, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
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