Applied ML Engineer

About This Opportunity

We are representing a confidential AI technology organization seeking an Applied ML Engineer based in Germany. This role sits at the intersection of machine learning research, experimentation, and production engineering. You'll transform research concepts into rigorous experiments, measurable evidence, and reliable systems that users can trust.

Working hands-on with modern ML models, you'll design evaluations that reveal what methods can and cannot demonstrate, while building production-grade tooling that makes complex experiments repeatable, observable, and accessible. The position spans model evaluation, model internals, inference infrastructure, backend systems, and user-facing product experiences.

Responsibilities

• Reproduce and evaluate machine learning research methods using open-weight and API-accessible models
• Design evaluation datasets, probes, scoring approaches, baselines, calibration tests, and experiment harnesses
• Work directly with model weights, logits, hidden states, activations, model APIs, and inference infrastructure
• Build and extend evaluation infrastructure covering experiment runners, judges, persistence, orchestration, reporting, and reproducibility
• Turn research workflows into intuitive product experiences, including experiment configuration, execution, traces, comparisons, and reports
• Investigate how verification methods behave when models are modified through fine-tuning, merging, quantization, distillation, or deliberate evasion
• Design controlled experiments that distinguish meaningful signals from artifacts, confounders, and misleading correlations
• Produce clear technical reports separating measured evidence from interpretation and hypotheses
• Deliver production-quality systems with APIs, asynchronous jobs, databases, observability, testing, deployment, and documentation
• Contribute across research, experimentation, engineering, and product as priorities evolve

What We're Looking For

Required Skills:

• Strong Python engineering skills with hands-on experience using PyTorch and Hugging Face Transformers
• Solid understanding of ML evaluation including dataset design, baselines, metrics, calibration, false positives/negatives, statistical uncertainty, and reproducibility
• Ability to read ML research papers critically and implement methods from first principles
• Professional software engineering experience beyond notebooks: APIs, asynchronous jobs, databases, logging, testing, deployment, and documentation
• Familiarity with open-weight models and practical understanding of modern LLM inference systems
• Ability to work across backend and frontend boundaries, with sufficient React/TypeScript knowledge to make complex experiments understandable to users
• Strong experimental and analytical judgment, particularly around distinguishing what evidence demonstrates versus what it suggests
• High ownership and initiative, with ability to identify problems, propose solutions, and drive projects independently
• Comfort working in a fast-moving startup environment where priorities change quickly

Beneficial Experience:

• Model provenance, fingerprinting, watermarking, distillation detection, red-teaming, safety evaluation, or interpretability
• Activation and representation analysis, probing, model hooks, logits, hidden states, or model-internals techniques
• Evaluation and inference infrastructure such as DSPy, LiteLLM, Temporal, Ray, vLLM, PostgreSQL/pgvector
• Next.js, React, TypeScript, data visualization, or experiment dashboards
• Running and serving open-weight models on GPUs, including reasoning about latency, throughput, memory, precision, and cost trade-offs
• Designing adversarial evaluations or testing systems against deliberate evasion attempts

How We Work With You

Our talent team at Get A Job.ai manages the application process on behalf of our client. Here's what to expect:

• Submit your application directly through the Get A Job.ai platform
• A dedicated recruiter will review your qualifications and conduct an initial screening
• Qualified candidates will be presented to our client for consideration
• Our client will conduct interviews and make final hiring decisions
• Please do not attempt to contact the client directly, as all communication is coordinated through our team

Pay

Compensation details will be discussed during the screening process based on experience and qualifications. Additional benefits may include healthcare, flexibility, and other perks according to the employer's package and German employment standards.

Equal Opportunity: Get A Job.ai is committed to fair and objective candidate evaluation. We use skills-based matching to ensure every application receives proper consideration regardless of background.