Machine Learning Engineer
Amsterdam, Netherlands
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDevelop bid estimation and margin-optimization models for the dynamic pricing engine
Build predictive models of carrier behavior and market capacity
Maintain and improve existing recommender systems
Explore ML approaches to freight routing and network optimization
Take prototypes through to production release and monitoring
From the employer’s posting
Develop and iterate on bid estimation algorithms and margin-optimization models to power our dynamic pricing engine
Build robust predictive models to forecast carrier behavior and market capacity
Maintain and improve our existing recommender systems
Explore and validate new areas where machine learning can solve fundamental logistics challenges (such as freight routing and network optimization)
maintaining an end-to-end attitude that covers the entire lifecycle from initial R&D and prototyping all the way through to production release and monitoring
Tools in this posting
- Python
- SQL
- Power BI
- Snowflake
- Streamlit
Source — Tool mentions in context
- ML Engineering: Experience deploying models to production environments, writing modular code, and understanding software engineering best practices. - Technical Skills: Strong proficiency in Python, SQL, and Git. Experience working with cloud data warehouses (e.g., Snowflake), utilizing Jupyter Notebooks for data exploration, and building interactive data apps/dashboards (e.g., Streamlit, PowerBI) to visualize outcomes for stakeholders. - AI Proficiency: A solid understanding of how to set up, evaluate, and leverage Large Language Models (LLMs) and related AI tools in a production setting.
Posting record
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- Live
- First seen by us
- Aug 13, 2026 · 78 days ago
- Recorded sightings
- 68
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
- Pricing Engine Optimization: Develop and iterate on bid estimation algorithms and margin-optimization models to power our dynamic pricing engine, directly driving company profitability.
- Carrier Forecasting: Build robust predictive models to forecast carrier behavior and market capacity, enabling our operational teams to secure the right trucks at the right price before the market shifts.
- Recommender Systems: Maintain and improve our existing recommender systems to seamlessly support our operational teams' day-to-day efficiency.
- Industry Innovation & Applied ML: Explore and validate new areas where machine learning can solve fundamental logistics challenges (such as freight routing and network optimization), turning open-ended industry problems into scalable, data-driven solutions.
- Product Discovery & Ideation: Partner closely with Product Managers to drive continuous product discovery, translating ambiguous operational pain points into clear, outcome-driven ML hypotheses and rapid prototypes.
- AI & LLM Integration: Leverage foundational models and AI agents both as daily accelerators for your own engineering workflows and as core components to build new internal products. We expect you to pragmatically evaluate trade-offs and always choose the right solution for the right problem—whether that is an LLM, a traditional ML model, or a simple heuristic.
- Platform Collaboration: Partner with our Data & AI Platform (MLOps) team to utilize and deploy models via our internal ML infrastructure. You will act as a key customer of this platform, providing continuous feedback and contributions to shape our global engineering standards.
- End-to-End Execution: Adopt a holistic approach to project deployment, maintaining an end-to-end attitude that covers the entire lifecycle from initial R&D and prototyping all the way through to production release and monitoring.
- Experience: 5+ years of hands-on experience in Data Science or Machine Learning Engineering.
- Data Science Fundamentals: Strong foundation in statistical analysis, hypothesis testing, and deep data exploration to validate assumptions and commercial viability before building complex models. You must possess a working knowledge of ML approaches to address basic regression and classification problems.
- ML Engineering: Experience deploying models to production environments, writing modular code, and understanding software engineering best practices.
- Technical Skills: Strong proficiency in Python, SQL, and Git. Experience working with cloud data warehouses (e.g., Snowflake), utilizing Jupyter Notebooks for data exploration, and building interactive data apps/dashboards (e.g., Streamlit, PowerBI) to visualize outcomes for stakeholders.
- AI Proficiency: A solid understanding of how to set up, evaluate, and leverage Large Language Models (LLMs) and related AI tools in a production setting.
- Business Acumen: Ability to translate complex & multifaceted logistical problems into data-driven solutions, prioritizing 'Outcome over Output'.
- Collaboration: Strong communication skills to work closely with Product Managers, end-users, and a diverse team of ML Engineers, Data Scientists and Platform Engineers.
- Impact: Build the data and AI foundation for Europe’s leading digital freight platform, at the moment sennder is shifting from buy-and-build to outcome-driven and AI-native.
- Vibrant Workspaces: Our offices are equipped with healthy snacks, focus zones, and social areas to keep you energized and connected. Highlights include a slide in our Wroclaw office and a sunny rooftop terrace in Berlin, Amsterdam, and Milan.
- Culture: Work in a fast-paced, hybrid environment with 1,100 talented, diverse colleagues from 74 nationalities. We prioritize well-being through initiatives like our sennCare program and a partnership with nilo.
- Growth & Rewards: We believe in rewarding our team for their commitment and contributions to our long-term success. Our compensation package may include performance bonuses, referral rewards, or equity that align with our goal of building a thriving company together.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Amsterdam, Netherlands
- Vibrant Workspaces: Our offices are equipped with healthy snacks, focus zones, and social areas to keep you energized and connected. Highlights include a slide in our Wroclaw office and a sunny rooftop terrace in Berlin, Amsterdam, and Milan. - Culture: Work in a fast-paced, hybrid environment with 1,100 talented, diverse colleagues from 74 nationalities. We prioritize well-being through initiatives like our sennCare program and a partnership with nilo. - Growth & Rewards: We believe in rewarding our team for their commitment and contributions to our long-term success. Our compensation package may include performance bonuses, referral rewards, or equity that align with our goal of building a thriving company together.
- Work authorization
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