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Shape is a startup that was created by the industry, for the industry. Our mission is to rethink operations for the digital age, making it more efficient, more transparent, and safer. A core part of this transformation is to optimize and automate how people make decisions.
With the advent of the Internet of Things, workers in the industrial sector started to have access to a huge amount of data. However, most still do not have the tools to make good use of it: going from data to insight, and from insight to action is a time-consuming and error-prone process. Our Machine Learning-enabled products address these gaps.
We are hiring someone who will help build Shape’s MLOps platform along with other MLEs. This platform is a strategic asset for the company, as we currently have close to a thousand models running in production - a figure that is growing fast. Our platform is built in Python, which means that having experience with this language is a must.
A strong candidate will have a solid software engineering foundation (clean code, git, CI/CD, automated testing, code modularization, python package construction) above all else. Prior work experience with Machine Learning is not a strict requirement, though we will expect that the candidate is interested in the area and motivated to learn fast. You will
- Help deliver models using advanced ML techniques to customers of multiple industries and at scale.
- Support the automation of the Machine Learning lifecycle, including training, testing, monitoring, and deployment.
- Research and implement new tools to improve model management and the overall productivity of the Data Science team.
- Design and develop innovative Machine Learning systems that power our data products.
- Has a strong software engineering background, knowledge of the best coding practices and experience delivering code for products.
- Is proficient with the Python language.
We are looking for someone who
- Has some knowledge of Machine Learning, and its relevant tools and frameworks (e.g., scikit-learn, Tensorflow, MLflow), even if outside the professional environment: courses, side projects, and self-study all count. We are looking for people who are excited about the topic even if still inexperienced.
- Learns fast and can work in a lean, autonomous, high-performance team.
- Writes code to solve problems targeting the product evolution, and not only the current state of the business. We expect people to be results-oriented, not task-oriented.
- Fosters an open and highly collaborative work environment.
Nice to have
- Experience in contributing to open-source software or working in code projects developed in collaboration with others.
- Hands-on experience building, deploying, and scaling the use of Machine Learning models to drive business impact. Both predictive and recommendation models are very relevant to what we do.
- Experience with models’ deployment to production environments and related tools (e.g., Docker, Kubeflow).
- Experience with big data tools (e.g., Apache Spark, Apache Kafka) and/or ETL pipelines development.
- Experience working in multidisciplinary agile product teams with flat hierarchical structures.
- PPR: varies according to the professional's performance and the company's profits;
- Health plan: expandable to dependents without co-payment or payroll deductions for themselves or their dependents;
- Dental Plan: expandable to dependents without co-participation or payroll deduction for themselves or their dependents;
- Life Insurance: no co-payment or payroll deduction;
- VA/VR: Transferred to the Flash benefits card;
- Corporate education incentive: we are finalizing the points regarding this benefit;
- Daycare allowance: for dependents up to 5 years old;
- Referral program: program to refer professionals in which the new Shaper is contemplated after his/her referral completes 3 months of service;
- Mentoring: with Shape leadership, aiming career development.