Super.AI
Machine Learning Engineer(m/w/x)
Full-timeWith HomeofficeExperienced
Berlin
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BIBioptimus
AI Technical Operations Manager(m/w/x)
Berlin
Full-timeWith Home OfficeExperienced
AI/ML
Data Science
Nejo AI Summary
Building agentic/LLM solutions for a universal AI foundation model at a biomedicine AI developer. Hybrid applied ML engineer/MLOps builder mindset with 2-5 years experience required. Equity package.
Requirements
- ML intuition, engineering capability, product mindset, and strong communication skills
- Hybrid applied ML engineer, MLOps builder, product thinker
- Thriving in ambiguous environments
- STEM degree or dual-degree blending business and ML/data science
- 2–5 years in applied ML, AI/data consulting, ML engineering, or MLOps
- Proficiency in Python and SQL
- Experience with Docker, AWS, CI/CD, and deploying ML systems
- Experience building and deploying ML models
- Ability to evaluate and debug ML systems using appropriate metrics
- Experience delivering ML or automation projects end-to-end
- Familiarity with LLMs, prompting, RAG, orchestration, fine-tuning
- Experience building agentic or multi-step LLM systems
- Working knowledge of vector databases
- Experience with workflow automation platforms
- Exposure to RL concepts
- Experience in client-facing AI/ML consulting engagements
Tasks
- Understand business workflows and requirements
- Design systems to address operational challenges
- Build agentic and LLM solutions
- Deploy and monitor solutions in production
- Iterate based on performance feedback
- Design and implement production-grade agentic systems
- Build multi-step agents using LLMs and orchestration frameworks
- Integrate classical ML models into workflows
- Deploy ML models in production environments
- Create generative AI components as needed
- Optimize prompts and retrieval strategies
- Ensure stability and reliability of automations
- Partner with various departments to identify automation opportunities
- Translate business needs into technical specifications
- Evaluate ROI and feasibility of solutions
- Manage solutions through the full lifecycle
- Communicate technical decisions to stakeholders
- Build CI/CD pipelines for models and tools
- Deploy services using Docker and AWS
- Implement evaluation frameworks for system performance
- Monitor systems for drift and degradation
- Maintain well-documented codebases and diagrams
- Track technological trends for build vs. buy decisions
- Train end-users on new systems and gather feedback
- Refine workflows with business functions
- Advise leadership on automation and architecture
- Build systems that enhance company operations
- Translate complex workflows into AI/ML systems
- Shape automation strategy within an AI lab
Work Experience
- 2 - 5 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- SQL
- Docker
- AWS
- CI/CD
Benefits
Flexible Working
- Flexible work arrangements
- Remote options
Competitive Pay
- Competitive salary
- Equity package
Career Advancement
- Opportunities for professional growth
- Leadership development
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bioptimus and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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BIBioptimus
AI Technical Operations Manager(m/w/x)
Berlin
Full-timeWith Home OfficeExperienced
AI/ML
Data Science
Nejo AI Summary
Building agentic/LLM solutions for a universal AI foundation model at a biomedicine AI developer. Hybrid applied ML engineer/MLOps builder mindset with 2-5 years experience required. Equity package.
Requirements
- ML intuition, engineering capability, product mindset, and strong communication skills
- Hybrid applied ML engineer, MLOps builder, product thinker
- Thriving in ambiguous environments
- STEM degree or dual-degree blending business and ML/data science
- 2–5 years in applied ML, AI/data consulting, ML engineering, or MLOps
- Proficiency in Python and SQL
- Experience with Docker, AWS, CI/CD, and deploying ML systems
- Experience building and deploying ML models
- Ability to evaluate and debug ML systems using appropriate metrics
- Experience delivering ML or automation projects end-to-end
- Familiarity with LLMs, prompting, RAG, orchestration, fine-tuning
- Experience building agentic or multi-step LLM systems
- Working knowledge of vector databases
- Experience with workflow automation platforms
- Exposure to RL concepts
- Experience in client-facing AI/ML consulting engagements
Tasks
- Understand business workflows and requirements
- Design systems to address operational challenges
- Build agentic and LLM solutions
- Deploy and monitor solutions in production
- Iterate based on performance feedback
- Design and implement production-grade agentic systems
- Build multi-step agents using LLMs and orchestration frameworks
- Integrate classical ML models into workflows
- Deploy ML models in production environments
- Create generative AI components as needed
- Optimize prompts and retrieval strategies
- Ensure stability and reliability of automations
- Partner with various departments to identify automation opportunities
- Translate business needs into technical specifications
- Evaluate ROI and feasibility of solutions
- Manage solutions through the full lifecycle
- Communicate technical decisions to stakeholders
- Build CI/CD pipelines for models and tools
- Deploy services using Docker and AWS
- Implement evaluation frameworks for system performance
- Monitor systems for drift and degradation
- Maintain well-documented codebases and diagrams
- Track technological trends for build vs. buy decisions
- Train end-users on new systems and gather feedback
- Refine workflows with business functions
- Advise leadership on automation and architecture
- Build systems that enhance company operations
- Translate complex workflows into AI/ML systems
- Shape automation strategy within an AI lab
Work Experience
- 2 - 5 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- SQL
- Docker
- AWS
- CI/CD
Benefits
Flexible Working
- Flexible work arrangements
- Remote options
Competitive Pay
- Competitive salary
- Equity package
Career Advancement
- Opportunities for professional growth
- Leadership development
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bioptimus and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Bioptimus
Industry
Other
Description
The company is building the first universal AI foundation model for biology to fuel breakthrough discoveries and accelerate innovation in biomedicine.
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