LIFELENZ is building a machine learning-based, advanced analytics workforce and human capital management platform to solve challenges related to onboarding, sales & labour forecasting, scheduling & time clock/keeping, insights & reporting and labour law compliance. The platform uses machine learning to automatically self-tune and self-manage models to a particular store with hyper-local attributes.
Requirements
- 4+ Years experience with python and machine learning frameworks
- 1+ year experience with MLOps and maintaining machine learning models at scale
- Extensive experience with Python programming language.
- Proficiency with relational database concepts, SQL, and a working knowledge of ETL processes.
- Experience with cloud technologies such as AWS, GCP, or Azure.
- Experience with version control systems (e.g., Git).
- Versioning and Tracking Models and Experiments (e.g. DVC, MLFlow)
Responsibilities
- Build and test machine learning models to support the LIFELENZ platform
- Design, build, and deploy data and machine learning pipelines on AWS
- Enable an iterative lifecycle for data products to continuously improve, integrate and deploy
- Bring data science workflows, analysis, and modeling into a healthy state of standardization, evaluation, deployment and observability in production.
- Build observability and monitoring of ML models & experiments
- Work collaboratively across teams to ensure a holistic MLOps process connecting modeling with engineering standards
- Embrace a dynamic startup environment
Other
- Bachelor's or Master's degree in Computer Science, Data Science , Mathematics, Statistics, Engineering, or a relevant field with 2-4 years of experience.
- Be an aspiring individual who enjoys variety and unpredictability in a role.
- Thrive in a fast-paced environment with demonstrated ability to quickly learn and adapt to new processes, tools, and software engineering concepts.
- Demonstrate tenacious problem-solving and critical thinking skills, attention to detail and a passion for driving efficient and scalable solutions.
- Be a self-starter and naturally curious individual who thrives in a dynamic work environment on individual initiatives, and as part of a team.
