Manager, Data Science Lisboa

Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in
- time, driving efficiency and agility.

Trusted by a community of 400, 000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s
- changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com.

Ultimately, Workato believes in fostering a flexible,
- oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.

But, we also believe in balancing productivity with
- care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.

If this sounds right up your alley, please submit an application. We look forward to getting to know you!

Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world

Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America

Quartz ranked us the #1 best company for remote workers

Responsibilities

• We are seeking an experienced Data Science / Machine Learning Engineering Lead to join our team and drive the development of advanced ML/AI capabilities. You will lead a team of Data Scientists / ML Engineers, focusing on building and deploying
  - edge machine learning solutions using our modern ML infrastructure including Anthropic, Open
  AI, and
  - hosted LLMs.
• Lead, mentor, and develop a team Data Scientists, Data Engineers, ML Engineers
• Conduct regular 1:1s, performance reviews, and career development planning
• Foster a collaborative, innovative team culture focused on continuous learning
• Coordinate work allocation and ensure timely delivery of projects
• Facilitate knowledge sharing and best practices across the team
• Technical Leadership — Design and implement scalable ML model training pipelines using modern toolset (e. g. MLflow, Comet, Langfuse, Wand
  B, Trino, dbt, Spark, Flink)
• Lead
  - tuning initiatives for both commercial (Anthropic Claude, Open
  AI GPT) and
  - source LLMs
• Utilise
  - hosted LLM infrastructure using Ray, AIBrix, and v
  LLM for optimal performance and cost efficiency with Lo
  RA/QLo
  RA
• Architect and oversee model continual validation frameworks within our ecosystem
• Develop
  - time anomaly detection systems leveraging streaming data processing
• Build predictive models for system performance, usage patterns, and automation workflow optimization
• Establish ML engineering best practices for model versioning, monitoring, and deployment on Kubernetes
• Creation of eval, validation and metrics pipelines for models during training and inference
• Strategic Initiatives — Optimize the balance between commercial APIs (Anthropic, Open
  AI) and
  - hosted models for different use cases
• Partner with product and engineering teams to identify
  - impact ML opportunities
• Define the team's technical roadmap aligned with company objectives
• Drive adoption of
  -
  -
  - art ML techniques and tools
• Contribute to infrastructure decisions for scaling our ML platform
• Operational Excellence — Implement robust CI/CD pipelines for ML models in Kubernetes environments
• Monitor model performance using MLflow tracking and implement drift detection
• Manage Flink jobs for
  - time feature engineering and anomaly detection
• Document processes, architectures, and decision rationale

Qualifications / Experience / Technical Skills

Education & Experience

• Master's or Ph
  D in Computer Science, Machine Learning, Statistics, or related field
• 10+ years of
  - on experience in data science/machine learning
• 5+ years of experience leading technical teams
• Proven track record of deploying ML & LLM models to production at scale

Technical Skills

• Deep expertise in Python and ML frameworks (Py
  Torch, Tensor
  Flow)
• Extensive experience with commercial LLM APIs (Anthropic Claude, Open
  AI GPT-4)
• Strong proficiency with MLflow for experiment tracking and model management
• Experience with distributed computing using Apache Spark
• Proficiency with Apache Flink for stream processing and
  - time ML
• Knowledge of LLM
  - tuning techniques (Lo
  RA, QLo
  RA, full
  - tuning)
• Expertise in anomaly detection algorithms and time series analysis

Leadership Skills

• Demonstrated ability to lead and inspire technical teams
• Strong communication skills to translate complex technical concepts to stakeholders
• Experience with agile development methodologies
• Track record of successful
  - functional collaboration
• Ability to balance technical excellence with business pragmatism

Soft Skills / Personal Characteristics

• Experience with AIBrix, vllm or similar ML platform solutions
• Experience with AI code generation and anonymisation pipelines
• Knowledge of advanced prompting techniques and prompt engineering
• Experience building RAG (Retrieval Augmented Generation) systems
• Background in building ML platforms or infrastructure
• Familiarity with vector databases (Pinecone, Weaviate, Qdrant)
• Experience with model security and responsible AI practices
• Contributions to
  - source ML projects

(REQ ID: 2252)