ML Engineering Manager in Constanţa

People Management (regular) AWS (regular) Python (advanced) Machine Learning (advanced) Data Science (advanced) PeakData is a Swiss-based AI startup on a mission to alleviate the burden of medical affairs and commercial teams as they pave the way for new therapies and treatments from KOL engagement to commercialization. Since its founding in 2017, the company has shown steady success through its product Healthscape – a one-stop platform that consolidates public and proprietary data about KOLs and prescribers in real-time. One of our main challenges is in obtaining real-time insights from publicly available data sources such as social media, open web, research and medical publications, and many others. We are looking for an ML Engineering Manager to lead the development of our different ML models and solutions from end to end, including the integration with other teams' services and products. The area of our ML models is primarily focused on NLP.  You will: Empower your team and create a safe and inclusive environment, helping people grow personally and professionally. Coach and guide the team to deliver effective and be accountable for the team outcome. Provide methodical guidance to the team and establish best practices that lead to reliable ML-based products and a productive team. Support the team in identifying the right level of research vs results delivery and the right boundary between models complexity vs its value to the business. Identify and tackle existing problems, and have difficult conversations and decisions to move your team and the company forward. Collaborate with product managers and product owners on topics and task prioritization. Supports the product roadmaps, by defining an executable engineering roadmap that your team can deliver on. Coordinate team activities with other product teams and platform teams. Optimize team settings and collaborate with recruitment to attract the best talent to your team and the company. Work on very interesting and innovative data product which includes real-world web data at scale. Work on solving challenging problems in the NLP field.  You are: You Have experience of at least 5 years as an ML Engineer / Data Scientist and at least 2  years as a Data Science / ML Engineering Manager. You are not afraid to be hands-on and deep dive into the code when it's needed. You Have experience working and leading cross-functional ML teams in an Agile environment, preferably using Scrum or Kanban. You have a passion for building, leading and nurturing successful data science and ML engineering teams.  You have a solid understanding of Python (including standard Data Science libraries), SQL, and large-scale processing engines (e.g. Spark).  You Have experience with different data analytics and statistical methodologies. You Have experience with the AWS ecosystem (e.g. S3, Glue, Lambda, RedShift, SageMaker). You have Experience delivering production-grade ML/NLP models in real-time (REST APIs, microservices) and in a batch fashion. You are familiar with MLOps best practicesPragmatic - you know when to make a cut for ongoing discussions and start working on deliverables. Communicative - you make your voice heard among the team and the wider tech organization and engage with our stakeholders to enable them and listen to their needs.Have an entrepreneurial mindset. You are able to deal with ambiguity and help to identify new opportunities and required improvements. Have excellent written and verbal communication (English).  Bonus points if you are: Have familiarity with serverless architectures. Have familiarity with SQL and No-SQL databases.  Have familiarity with Jira. Scrum master certification. Have Previous experience working remotely.  Have Previous experience in pharma.  Recruitment process:  HR Screening.Cultural fit interview – 45 minutes.  Tech interview - 75 minutes. Leadership interview – 30 minutes.   Team size / seniority / team structure:  The team size is going to be up to 8 engineers. Mixed level of seniorities.The team consist of MLOps, ML engineers, Python developers, and a Product Manager.