AI Engineer, Business and Engineering efficiency
vor 16 Stunden
Introduction: A Career at HARMAN Automotive
We're a global, multi-disciplinary team that's putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.
- Engineer audio systems and integrated technology platforms that augment the driving experience
- Combine ingenuity, in-depth research, and a spirit of collaboration with design and engineering excellence
- Advance in-vehicle infotainment, safety, efficiency, and enjoyment
About the Role
We are seeking an AI Engineer to join the Harman Automotive AI Lab. In this role, you will design, implement, and productize advanced machine learning systems to enhance engineering workflows and drive operational efficiency across Harman Automotive.
As part of the AI Lab, you will work closely with cross-functional teams to build scalable, cloud-native ML solutions that address real-world challenges in engineering and operations.
What You Will Do
Translate business and technical requirements into effective machine learning solutions.
Design, implement, and deploy production-grade ML models and systems, with a focus on reliability, scalability, and maintainability.
Conduct experiments, evaluate new algorithms and techniques (including LLMs and GenAI), and bring innovative approaches to productization.
Build and maintain robust data and ML pipelines, from data ingestion to model serving, using modern cloud-native architectures.
Monitor and optimize deployed ML systems for performance, robustness, and business impact.
Contribute to the development of MLOps practices, including reproducibility, CI/CD for ML, and automated monitoring.
Collaborate with other ML engineers, data scientists, and software engineers to deliver impactful, high-quality AI solutions.
Stay current with recent research and advancements in ML/AI, especially in generative AI, and evaluate their practical application to our domain.
What You Need to Be Successful
- Master's degree in Computer Science, Machine Learning, or a related field.
- 5+ years of hands-on experience building and deploying ML systems in production environments.
- Strong experience with cloud platforms (AWS, Azure), including services for data processing, training, and model deployment.
- Proficiency in Python and core ML libraries (e.g., PyTorch, TensorFlow, scikit-learn).
- Solid understanding of machine learning system design: pipelines, model lifecycle, performance tuning, and monitoring.
- Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker, etc.).
- Familiarity with LLMs, prompting techniques, and inference strategies for GenAI solutions.
- Strong software engineering skills: object-oriented design, version control, unit testing, and clean code principles.
- Ability to work independently and collaboratively in a fast-paced, cross-functional environment.
What Makes You Eligible
- Willingness to travel up to 10%, domestic and international travel
What We Offer
HARMAN offers a diverse and inclusive work environment that fosters and encourages career development opportunities, professional training and competitive market base compensation
You will also receive top-notch employee discounts on Harman's Consumer Audio (JBL, AKG, HARMAN Kardon) and Samsung products
Flexible work schedule with a culture encouraging work life integration and collaboration in a global friendly working atmosphere and good work-life-balance
Attractive salary package based on the Metall & Elektro Tarif Baden Wurttemberg and an Employer contribution towards a company pension plan
Professional development opportunities through HARMAN University's business and leadership academies which also includes extensive technical trainings
Internal talent management leadership acceleration programs
"Be Brilliant" employee recognition and rewards program
#LI-Hybrid
HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, 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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