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Engineering Manager - Machine Learning

aignostics.com Logo

Aignostics

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Location:
Germany , Berlin

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

As a ML Engineering Team Lead at Aignostics, you will lead a high-performing team focused on building large-scale distributed training infrastructure and workflows using cutting-edge technologies for digital pathology, powering our state-of-the-art Foundational Model development. This is a hands-on leadership role where you'll spend approximately 50% of your time on technical contributions while guiding your team to push the boundaries of machine learning for cancer research and diagnostics. You'll own the full employee lifecycle for your team, drive technical roadmapping and ensure operational excellence while fostering a culture of autonomy and innovation.

Job Responsibility:

  • Build and scale a high-performing team capable of tackling complex distributed ML challenges
  • Own the full employee lifecycle: recruiting, onboarding, performance management, career development, and retention
  • Empower your team members and help them grow in autonomy and technical expertise
  • Mentor engineers at all levels
  • Create an inclusive environment where diverse perspectives drive innovation
  • Define and execute technical roadmaps aligned with company objectives and product needs
  • Lead resource allocation and capacity planning
  • Own FinOps responsibilities: optimize cloud costs, track spending, and ensure efficient resource utilization
  • Ensure operational readiness through monitoring, incident response protocols, and system reliability practices
  • Establish and track KPIs for team performance, system efficiency and health
  • Design, develop, and maintain robust large-scale distributed training pipelines and ML infrastructure
  • Lead architecture decisions for distributed systems
  • Hands-on contribution to critical technical challenges
  • Drive technical excellence through code reviews and architectural guidance
  • Stay at the forefront of distributed training technologies
  • Partner closely with Product teams to translate business requirements into technical solutions
  • Collaborate with (senior) Research Scientists
  • Work with Platform Engineering to ensure robust infrastructure and tooling
  • Build strong relationships across engineering teams
  • Communicate technical concepts effectively to both technical and non-technical stakeholders

Requirements:

  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
  • 6+ years of software engineering or ML engineering experience, with at least 2 years in a technical leadership or team lead role
  • Proven track record of building and leading high-performing engineering teams
  • Experience guiding projects across the whole Software Development Life Cycle
  • Deep understanding of fundamental Machine Learning concepts and principles
  • Familiarity with advanced model optimization techniques
  • Significant experience with large-scale distributed training systems and frameworks (especially PyTorch and NCCL)
  • Familiarity with GPUs, distributed systems, parallel computing and scaling laws
  • Advanced programming skills in Python
  • Familiarity of MLOps/DevOps best practices including CI/CD, Docker, Kubernetes, and observability
  • Experience with cloud platforms (GCP, AWS or Azure) and infrastructure-as-code
  • Experience with Linux, version control, and container technologies
  • Demonstrated ability in resource allocation, capacity planning, and FinOps principles
  • Excellent problem-solving and data-driven decision-making skills in ambiguous situations
  • Effective communication and stakeholder management skills
  • Ability to give constructive feedback and navigate difficult conversations
  • Proven people leadership skills with experience managing the full employee lifecycle
  • Strategic thinking with ability to balance short-term execution and long-term vision
  • Experience with agile methodologies and iterative development processes
  • Proven ability to influence without authority and build consensus across teams
  • Track record of empowering team members and fostering autonomy

Nice to have:

  • Experience with production systems in a regulated or healthcare environments
  • Familiarity with medical device standards (ISO 13485)
  • Experience working with biomedical or image data
  • Hands-on experience with Google Kubernetes Engine, SLURM and Ray distributed computing framework
  • Experience with advanced ML stack (TorchDyno, JAX, TensorRT)
  • Familiarity with Information Security standards (ISO 27001) in software development
  • Experience with FinOps tools and cloud cost optimization strategies
  • Demonstrated experience with leveraging LLM/Agentic systems to accelerate development
What we offer:
  • Learning & Development yearly budget of 1,000€ (plus 2 L&D days)
  • Language classes
  • Internal development programs
  • Access to leadership development programs and executive coaching
  • Flexible working hours and teleworking policy
  • 30 paid vacation days per year
  • Family & pet friendly
  • Support flexible parental leave options
  • Subsidized membership of your choice among public transport, sports, and well-being
  • Social gatherings, lunches, and off-site events
  • Optional company pension scheme

Additional Information:

Job Posted:
January 16, 2026

Work Type:
Hybrid work
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