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Ml Platform Engineer

il y a 7 heures

Paris, France Capital Fund Management Temps plein

Paris, 75, FR

**ABOUT CFM**:
We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.

**ML Platform team**:
The ML Platform team is focused on enhancing researcher productivity in training machine learning (ML) models by developing libraries, services, and best practices, and ensuring robust ML production at scale.

The aim is to provide a seamless path from experimentation to production that integrates with existing systems and boosts efficiency for model deployment.

The team mandate consists of addressing pain points, advancing organizational ML capabilities, and leveraging platform engineering with a modular, self-service approach.

It balances immediate user needs with sustainable technical decisions, emphasizing best practices and automation.

The team is composed of profiles working on cross-functional projects as well as engineers supporting functional teams in their ML journey.

**Your role**:
As a senior engineer, you will be expected to participate in all the individual contributions of the team but also weigh in and participate in all the major decisions about the technical trajectory of the team as well as its technical culture. You will also need to lead the interactions with some of the team's stakeholders, those closer to your area of expertise, in support of the Head of ML platform.

**In more detail**:

- Foster adoption of AWS, in general but also through the definition and development of quality-of-life components on the ML Platform in order to entice our users to migrate to cloud usage.
- Define standard practices for ML development, from experimentation to deployment, focusing on reproducibility, quality and auditability.
- Develop self-service tools and services to increase the throughput of ML development at CFM
- Support use cases on our on-premise, HPC, infrastructure.
- Mentor younger team members when the team will grow
- Train users and participate in a company wide effort towards industry best practices when it comes to ML related software development

**Your skills**:
**Mandatory**:
**_Technical_**:

- Extensive expertise in Python and general software development best practices.
- Experience working in environments that deploy ML solutions to production and address MLOps challenges.
- Proficient in using containerization technologies.
- In-depth experience with traditional ML and deep learning tools such as TensorFlow or PyTorch, MLFlow or similar platforms, and inference servers like Triton.
- Strong familiarity with UNIX-based systems.
- Experience with AWS services.

**_Work methodology_**:

- Experience with Agile, emphasizing flexibility and pragmatism over strict adherence.

**_Soft skills_**:

- Ability to articulate and defend strong opinions constructively, fostering consensus.
- Experience to understand not all decisions will go your way, with the ability to disagree yet commit.
- User-centered mindset while avoiding short-term solutions.
- Skill in engaging and motivating colleagues to adopt best practices.
- Commitment to team productivity and resilience through skill-sharing, beyond individual

**Nice to have**:
**_Technical_**:

- experience working with C and C++
- DevOps knowledge, especially for everything related to infra as code

**_Soft skills_**:

- having occupied a tech lead or engineering manager role

If you don’t meet every requirement but believe you’d be a great fit, feel free to reach out to us.

**EQUAL OPPORTUNITIES STATEMENT**:
We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success.
CFM is a signatory of the Women Empowerment Principles.