Team Leader, Machine Learning

Responsibilities

• Manage and mentor this team, facilitating both professional and technical development of team members
• Provide technical leadership by using your experience in the ML domain to advise on software design and ML/statistical solutions. Collaborate with the product team to comprehend high-value problems and counsel them on the feasibility and limitations of potential approaches
• Lead the assessment of various machine learning models and ascertain their relevance to specific analytics problems
• Oversee the development of ML algorithm-based product features; considerations include deployment, scalability, observability, and rollout
• Maintain post-production ownership of ML modules incorporated into the product
• Utilize an agile methodology to manage the team's software delivery
• Contribute to the growth of a new ML team from 0 to 4-5 members in the upcoming 6-9 months

Qualifications

• Over 2 years of experience leading an ML/Data Science team
• More than 5 years of ML/data science experience, demonstrating a high aptitude for resolving complex analytical problems in the ML/Data science domain
• At least 3 years of experience in delivering ML-based products and managing them in a production setting
• In-depth knowledge of machine learning (such as deep learning, ensemble methods, regression methods, time series analysis) and statistical methods
• Experience in leading the development of ML applications that handle large-scale data
• Capable of clearly, precisely, and actionably convey technical findings stemming from complex quantitative analyses
• Knowledge of Python and standard ML frameworks, like , TensorFlow, or Keras
• Knowledge of analysis tools and packages including NumPy and SciPy
• Experience with end-to-end ownership of ML features, incorporating productization, continuous performance monitoring, and ongoing improvements
• Understanding of architectural considerations, performance, parallelization, robustness, and fault mitigation
• Knowledge of (e.g. Postgres, MySQL) and NoSQL databases (e.g. MongoDB)
• Experience of working within a distributed organization, with a global presence
• Understanding of multi-threading and replication concepts in cloud applications would be an asset
• Experience with streaming frameworks such as Kafka, and Kinesis would be beneficial
• Experience in managing the model lifecycle with tools like SageMaker or MLflow would be advantageous
• Familiarity with K8S would be a plus

Perks and Benefits @ Clari

• Team bonding activities and company-wide events
• Flexible work hours and remote opportunities
• Annual Wellness and Professional Development Allowances
• Private Healthcare and Multisport Pass
• Paid maternity and paternity leave
• Stock options