Responsibilities
- Manage and coach this team, developing team members professionally and technically
- Provide technical leadership, leveraging your experience in the ML domain to advise on both software design and ML/statistical solutions. Work with the product team to understand key high-value problems and advise them on feasibility and limitations of possible approaches
- Lead the evaluation of various machine learning models and qualify their suitability to a specific analytics problem
- Lead development of ML algorithm-based product features, which includes considerations of deployment, scalability, observability, and rollout
- Maintain post-production ownership of ML modules incorporated into the product
- Use an agile methodology to manage delivery of software by the team
- Help to grow a new ML team from 0 to 4-5 members in the next 6-9 months
Qualifications
- 2+ years experience leading an ML/Data Science team
- 5+ years of ML/data science experience, demonstrating high aptitude in solving complex analytical problems in the ML/Data science domain
- 3+ years experience in delivering ML-based products and managing them in a production environment
- Deep knowledge of machine learning (e.g. deep learning, ensemble methods, regression methods, time series analysis) and statistical methods
- Experience in leading the development of ML applications dealing with large-scale data
- Ability to communicate technical findings based on complex quantitative analysis in a clear, precise, and actionable manner
- Knowledge of Python and standard ML frameworks such as PyTorch, TensorFlow, or Keras
- Knowledge of analysis tools and packages such as NumPy and SciPy
- Experience with end-to-end ownership of ML features, including productization, continuous performance monitoring, and ongoing improvements
- Understanding of architecture consideration, performance, parallelization, robustness, and fault mitigation
- Knowledge of SQL (e.g. Postgres, MySQL) and NoSQL databases (e.g. MongoDB)
- Experience working within a distributed organization, with a worldwide presence
- Experience with multi-threading and replication concepts in cloud applications is a plus
- Experience working with streaming frameworks such as Kafka, and Kinesis is a plus
- Experience managing the model lifecycle with tools like SageMaker or MLflow is a plus
- K8S familiarity is a plus
Perks and Benefits @ Clari
- Team-bonding activities and company-wide events
- Flexible working hours and remote opportunities
- Annual Well-being and Professional Development Stipends
- Private Healthcare and Multisport Pass
- Paid maternity and paternity leave
- Stock options
![Clari](https://storage.googleapis.com/echojobs.io/static/logos/1646195090-Clari.png)
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