Senior Machine Learning Engineer

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November 13

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DocPlanner

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Healthcare Insurance • SaaS • B2C

DocPlanner is a global healthcare platform dedicated to improving the patient experience by helping them find the perfect doctor and book appointments easily. By creating an enjoyable patient journey, DocPlanner assists patients in accessing the best care possible anytime and anywhere. The company also offers doctors an integrated end-to-end solution to help manage their practices and improve their online reputation, allowing them to focus more on their patients. With a presence in 13 countries, including Poland, Brazil, and Spain, DocPlanner facilitates over 22 million appointments each month and hosts more than 90 million patient visits. It supports 260,000 active doctors, making it a leading healthcare platform with a strong international footprint.

1001 - 5000 employees

Founded 2012

⚕️ Healthcare Insurance

☁️ SaaS

👥 B2C

📋 Description

• Take technical leadership of ML initiatives, working closely with scientists, engineers, and product stakeholders to deliver AI-driven solutions that directly support strategic business objectives • Design, deploy and iterate over ML services for diverse data types (e.g., audio, text), while proactively anticipating performance bottlenecks driving continuous improvements • Brainstorm and design technical roadmaps in partnership with the AI Platform team, identifying and addressing platform and MLOps bottlenecks, and designing scalable GPU optimization strategies that balance performance, cost, and reliability • Research, architect, and deploy LLM-powered information retrieval solutions (e.g., RAG) to deliver accurate and scalable results in complex, multilingual product environments; champion industry-leading frameworks and evangelize their adoption across the organization • Lead efforts to improve team effectiveness by evolving internal frameworks, optimizing workflows, and fostering a culture of operational excellence in collaboration with the AI Platform team • Architect, deploy, and maintain high-throughput, reliable data pipelines to support training-set curation and data-annotation tooling

🎯 Requirements

• 5+ years of professional experience as an ML[Ops] Engineer in a fast-paced, product-driven tech environment • Proven track record of delivering impactful ML initiatives in high-scale, cross-functional, and high-performance environments • Demonstrated expertise in production-grade MLOps, leveraging, for example, orchestration with Kubernetes, model serving via FastAPI, NVIDIA Triton and KServe, Apache Airflow for data pipelines • Good understanding and proficiency in deep learning frameworks such as PyTorch or TensorFlow • Proven ability to integrate, deploy, and optimize large language models in production-grade industry environments, ensuring scalability and robust performance • Knowledgeable in prompt engineering, basis of agent‐based workflows, and the generation and manipulation of embeddings • Problem-solving mindset and adaptability in dynamic environments with a focus on delivering business value to end customers • Strong collaboration and communication skills, with a track record of influencing cross-functional stakeholders and aligning diverse teams around shared goals • Proven ability to manage timelines, prioritize tasks, and deliver results under tight deadlines • Experienced in mentoring and guiding other engineers, fostering technical growth and promoting a high-performance team culture

🏖️ Benefits

• Flexible remuneration and benefits system via Flexoh, which includes: restaurant card, transportation card, kindergarten, and training tax savings • Share options plan after 6 months of working with us • Private healthcare plan with Adeslas for you and subsidized for your family (medical and dental) • Access to hundreds of gyms for a symbolic fee in partnership for you and your family with Wellhub • Access to iFeel, a technological platform for mental wellness offering online psychological support and counseling • 23 paid holidays, with exchangeable local bank holidays • Additional paid holiday on your birthday or work anniversary