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Senior Machine Learning Engineer

Pipedrive

Join Our Team as a Senior Machine Learning Engineer

Pipedrive is seeking an experienced Machine Learning Engineer to join our AI platform team in Tallinn. In this role, you will collaborate with a talented team on cutting-edge AI/ML projects to solve real-life customer problems using advanced AI/ML techniques.

Your New Adventure

  • Collaborate with cross-functional teams, including data engineers, data scientists, and analysts, to develop innovative machine learning product features.
  • Create robust and scalable processes for generating reliable models that provide accurate predictions and actionable insights to support business objectives.
  • Optimize ML models running in production for better performance, latency, memory, and throughput.
  • Ensure that models in production are monitored for performance and accuracy.
  • Ensure error-free and efficient deployments of models from development into an existing production infrastructure.
  • Ensure data privacy, security, and compliance with relevant regulations and best practices.
  • Help Pipedrive grow by leveraging data-driven approaches, optimizing processes, and identifying opportunities for innovation and efficiency improvement.

Does This Sound Like You?

  • Minimum of 3 years in data science and machine learning.
  • Strong understanding and hands-on experience in MLOps, including productionizing ML solutions.
  • Proficiency with production-ready ML frameworks and tools (e.g., Amazon SageMaker, PyTorch, ONNX Runtime).
  • Experience with LLMs and AIaaS providers such as OpenAI and Anthropic.
  • Ability to effectively communicate complex solution designs to non-technical stakeholders.
  • Proficient in Python, Typescript, and SQL.
  • Skilled in exploratory data analysis, feature engineering, and model evaluation.
  • Strong can-do attitude, excellent communication skills, and openness to feedback.
  • Fluent in English.
  • Goal-oriented with a focus on delivering high-quality results within deadlines.
  • Ability to thrive in a fast-paced, dynamic environment, adapting to changing requirements and priorities.
  • Passionate about continuous learning and staying updated with advancements in machine learning engineering.

Bonus Skills

  • Experience with distributed data processing systems such as Apache Spark.
  • Knowledge of prompt engineering.
  • Familiarity with the CRM domain.
  • BSc or MSc in Computer Science, Mathematics, Statistics, or a related field, or equivalent relevant experience.

Why Pipedrive?

  • A value-driven work environment where people come first.
  • A lively bunch of colleagues from over 50 different countries, with offices in Tallinn, Tartu, Lisbon, Prague, London, Dublin, New York, Florida, Riga, and Berlin.
  • A team serious about getting things done while not taking ourselves too seriously.
  • A world-class working environment full of perks like parties, craft workshops, snacks, and, of course, office dogs.
  • Flexible working hours as long as you’re there for your team members.
  • Freedom to execute your ideas with a passionate and motivated team supporting you.
  • Lots of room for personal and career development, with internal and external training opportunities.
  • Competitive salary and bonus system and all the benefits you’d expect from a great employer (health and accident insurance, health days, a quarterly contribution to sports, in-house coaches, employee discounts, and more).

Pipedrive is an equal-opportunity employer. We encourage diversity in the workplace regardless of age, gender, race, religion, disability, sexual orientation, gender identity, or veteran status.

Based on this role's access to certain data, Pipedrive might conduct a pre-employment background investigation in conjunction with your application for employment with our company. Such data will be handled in accordance with Pipedrive's Privacy Policy for Recruitment.

Benefits
Extracted with AI

  • Flexible working hours
  • Competitive salary and bonus system
  • Health and accident insurance
  • Quarterly contribution to sports
  • In-house coaches
  • Employee discounts
  • Internal and external training opportunities
  • Office dogs
  • Craft workshops
  • Snacks

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