Senior Applied AI / ML Engineer (f/m/x)

BMW Group; München; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Benefits dieser Stelle

Flexible working hours

Annual special payments

Discounted BMW & MINI conditions

6 weeks annual leave

Professional development opportunities

Zusammenfassung

A leading automotive company in Munich is searching for a Machine Learning Engineer to focus on AI applications in next-gen mobility. The role requires expertise in model engineering, particularly working with PyTorch and compressing models for efficient performance. Enjoy competitive remuneration, flexible working hours, and numerous perks such as vacation pay and profit sharing. Candidates should have a degree in a relevant field and several years of practical experience in machine learning.

Qualifikationen

• Several years of experience in applied machine learning and model engineering.
• Expertise in model compression, alignment, and fine-tuning of small GenAI and ML models.
• Practical knowledge of edge device constraints such as RAM and bandwidth.

Aufgaben

• Select and adapt base models for voice assistant and intelligence tasks.
• Produce clean, reproducible training and evaluation pipelines.
• Implement compression strategies to enable cost-efficient inference.

Kenntnisse

Applied machine learning

Model engineering

PyTorch

Transformers frameworks

Model compression

Statistical analysis

Knowledge of edge device constraints

Ausbildung

University degree in Computer Science, Engineering, or a related field

Jobbeschreibung

ARE YOU PREPARED FOR THE FUTURE? AI, AI SIR!

Artificial Intelligence and machine learning are at the cutting edge when it comes to shaping next-gen mobility in areas like automated driving. But it takes real intellectual leadership and expertise to identify and then harness the AI trends and technologies that will transform the way people travel for good.

We are an international team of experts shaping the future of intelligent mobility by developing and refining edge GenAI models for the BMW Intelligent Personal Assistant. Together, we deliver customer impact through innovative model engineering and robust data pipelines.

What awaits you?

• You select and adapt base models for voice assistant and intelligence tasks.
• Furthermore, you produce clean, reproducible training, finetuning and evaluation pipelines to refine models for the problem at hand.
• You implement required compression strategies such as quantization, pruning and distillation to enable cost-efficient inference.
• Additionally, you collaborate with performance engineers on hardware‑aware model variants and performance.
• You co‑own latency and memory KPIs and provide models that meet budget requirements on the target hardware.
• You document design choices, trade‑offs and model cards for audits and compliance.

What should you bring along?

• University degree in Computer Science, Engineering, or a related field.
• Several years of experience in applied machine learning and model engineering.
• Proficient in PyTorch and Transformers frameworks.
• Expertise in model compression, alignment, and fine‑tuning of small GenAI and ML models.
• Skilled in building evaluation suites and performing statistical analysis of model behaviour.
• Practical knowledge of edge device constraints such as RAM, bandwidth, cache, and cold start.
• Professional English proficiency, German is a plus.

What do we offer?

• Challenging projects with which we are shaping the mobility of tomorrow together.
• Wide range of personal and professional development opportunities.
• Attractive, fair and performance‑related remuneration.
• High level of job security.
• Annual special payments such as vacation pay, Christmas bonus, and profit sharing.
• Flexible working hours including 6 weeks annual leave and overtime compensation.
• Discounted BMW & MINI conditions.
• Many other benefits at bmw.jobs/benefits

Start date: from now on

Type of employment: unlimited

Working hours: FULLTIME

At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants.