Machine Learning Engineer Lead

Das ist der Job

What kind of challenges will you tackle with us?

Darum lohnt es sich

We work on a range of exciting projects from real‑time advertising systems to modern data stacks, always focused on solving real‑world challenges.

From startups to global corporations, these are some of the key areas we focus on: Building Modern Data Stacks Real‑Time Advertising Auction Systems Scalable Cloud Architectures Applied Machine Learning for Business Solutions Promotions & Pricing Optimization Check out our case studies.

Lead teams, collaborating with Machine Learning and data engineers. Champion the productization of ML models following MLOps best practices, including orchestration, testing, monitoring, and serving, to benefit our clients.

Familiarity with Modern Data Architectures, including the implementation of Data Warehouses and Data Lakes, as well as DevOps tool/stack and methodologies (CI/CD, Kubernetes, Docker, GitOps, etc.). Nice to have skills Experience with the Modern Data Stack. Remote‑first culture with flexibility, autonomy, and awesome benefits.

Massive benefits: Monthly credits to spend in our benefits marketplace. Referral bonuses to grow our team. Annual Mutters’ Trip – join us for an unforgettable team trip.

Apply now and join a team that’s shaping the future of Machine Learning and Data Engineering. #J-18808-Ljbffr We’re Mutt Data, a remote‑first startup crafting cutting‑edge Data Products and Machine Learning solutions for clients across the globe.

We build systems that power the future of business and help clients reach their full potential through the power of data. At Mutt Data, we’re solving complex, real‑world problems across industries. Now, we’re looking for a Machine Learning Engineer Lead to help us build and scale impactful solutions.

If you’re passionate about building systems, solving complex problems, and growing your expertise, let’s connect. Responsibilities Effectively manage projects by engaging with customers to understand the scope of work. Collaborate with Machine Learning Engineers to develop meaningful ML Proof of Concepts (POCs) for internal and client requirements.

Oversee the lifecycle of Machine Learning models, optimizing them when necessary to enhance performance, latency, memory, and throughput. Translate business and mathematical/statistical requirements into software implementations, making informed trade‑offs between time, quality, and client‑specific needs.

Explore emerging ML engineering technologies (Data Science, Data Engineering, DevOps) and techniques to enhance our toolset, best practices, and overall business value. Participate in defining project roadmaps, timelines, and estimates for new initiatives. Document and disseminate industry‑leading practices in AI/ML within the organization.

Collaborate on hiring interview processes (exam reviews and technical interviews). Safeguard information security, ensuring responsible data usage and compliance with best practices for protection and confidentiality. Required Skills Demonstrated leadership skills and experience in client interactions.

Demonstrated work experience in roles such as Machine Learning Engineer, ML Architect or similar. In‑depth understanding of AI/ML principles, encompassing neural networks, supervised and unsupervised ML models, time series forecasting, and more. Previous involvement with data processing ETL and ML workflows (Airflow, MLflow, DBT).

Understanding of Deep Learning frameworks and technologies such as Keras, PyTorch, TensorFlow. Strong grasp of Python programming language and proficiency in at least one other strongly typed language. Knowledge of mathematical modeling and proficient statistical intuition.

Experience in implementing Machine Learning‑based systems, including model lifecycle management, monitoring, and setting up MLOps pipelines from scratch. Ability to develop implementation plans by weighing the pros and cons of different alternatives. English Intermediate Level.

Hands‑on experience with cloud‑based AI services like AWS SageMaker, AWS Textract, GCP Vertex AI, or similar. Profound knowledge of software development methodologies. A positive problem‑solving attitude. Previous experience in client‑facing tech consultancy roles. A track record of delivering high‑quality solutions.

Certification in cloud platforms, such as AWS Machine Learning. Familiarity with Python data libraries like SQLAlchemy, Pandas, Polars, PySpark, Great Expectations, etc. Why Join Us? Paid AWS & Databricks certifications. Birthday off + extra vacation week (Mutt Week!). Even if you don’t meet every requirement, we’d love to hear from you!

Let us know why you think Mutt Data is the next step in your journey.