Machine Learning Engineer II
sennder
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See open jobs at sennder.See open jobs similar to "Machine Learning Engineer II" Earlybird Venture Capital.Software Engineering
Barcelona, Spain
- Develop and deploy NLP & LLM solutions: Build production-grade systems for email classification, entity extraction, and automated bidding strategies using modern transformer-based architectures and LLM APIs.
- Maintain and refine Recommendation Systems: Optimize existing recommender pipelines to ensure carriers are matched with the best loads.
- Engineer scalable ML pipelines: Design robust training and inference pipelines, ensuring your models are reliable, observable, and meet strict SLAs.
- Handle unstructured data at scale: Work with Data Engineering to turn messy logistics data (emails, PDFs, chat logs) into structured features.
- Drive the product strategy: Work closely with Product Managers and Operators to drive the adoption of ML-powered products and revolutionize the logistic industry.
- Drive experimentation: Implement A/B tests and offline evaluation frameworks to measure the real-world business impact of your models, favoring pragmatic solutions over theoretical complexity.
- Experience: 5+ years of experience as a Machine Learning Engineer or Data Scientist with a strong software engineering component.
- Applied ML Expertise: Solid grasp of NLP (Transformers, LLMs, HuggingFace) and Recommender Systems (collaborative filtering, learning-to-rank, two-towers architecture). You know when to use a simple regression and when to deploy a complex deep learning model.
- Software Engineering proficiency: Strong fluency in Python (incl. Scikit learn, pandas and backend designs), you write clean, modular, and testable code. Experience with API frameworks (FastAPI, Flask), containerization (Docker, Kubernetes) and ML frameworks (Tensorflow, PyTorch) is required. You are familiar with AWS, Terraform and datadog.
- Production Mindset: Experience deploying models to production environments. Familiarity with model serving tools (e.g., BentoML, MLFlow) and workflow orchestration (e.g., Flyte, Airflow) is a strong plus.
- Data Fluency: Advanced SQL skills and experience working with cloud data warehouses (e.g., Snowflake).
- Problem Solver: You are motivated by solving business problems, not just technical ones. You are comfortable navigating ambiguity and iterating fast to validate hypotheses.
- Excellent communication skills: with a comfort level in explaining technical trade-offs to diverse audiences ranging from developers to stakeholders.
- Familiarity with MLOps tools and practices, such as containerization (Docker, Kubernetes), model versioning systems, and infrastructure automation (e.g., Terraform).
- A background in advanced data engineering concepts such as real-time streaming, large-scale ETL workflows, or AI-specific data pipelines.
- Experience deploying models at scale and creating fault-tolerant architectures.
- Experience with reinforcement learning applications in pricing or revenue optimization, and knowledge of game theory, auction mechanisms, or marketplace dynamics, to collaborate with our 2nd ML team.
This job is no longer accepting applications
See open jobs at sennder.See open jobs similar to "Machine Learning Engineer II" Earlybird Venture Capital.
