Machine Learning DevOps, Pathway

Cloud and Compute Cluster

Salary not provided

AWS

Docker

Kubernetes

GCP

Python

Linux

Airflow

Tensorflow

Terraform

Jenkins

Azure

Prometheus

Kubeflow

Grafana

PyTorch

Sagemaker

loki

Mid and Senior level

Remote from Canada, Europe, US

Real-time data analysis

Be an early applicant

Real-time data analysis

21-100 employees

B2BArtificial IntelligenceEnterpriseDeep TechData Analysis

Be an early applicant

Salary not provided

AWS

Docker

Kubernetes

GCP

Python

Linux

Airflow

Tensorflow

Terraform

Jenkins

Azure

Prometheus

Kubeflow

Grafana

PyTorch

Sagemaker

loki

Mid and Senior level

Remote from Canada, Europe, US

21-100 employees

B2BArtificial IntelligenceEnterpriseDeep TechData Analysis

Company mission

To help software engineers to focus on developing code logic, without having to worry about the way data changes over time.

Job

Company

Role

Who you are

Very good familiarity with Linux, shell scripts, and cluster configuration scripts as the basic work tool
Proficiency in workload management, containerization and orchestration (Slurm, Docker, Kubernetes)
Solid grasp of CI/CD tools and workflows (GitHub Actions, Jenkins, Gitlab CI, etc.)
Cloud infrastructure knowledge (AWS, GCP, Azure) – especially in ML services (e.g., SageMaker Hyperpod, Vertex AI)
Familiarity with monitoring/logging tools (Grafana, CloudWatch, Prometheus, Loki)
Experience with infrastructure as code (Terraform, CloudFormation, cluster-toolkit)
Experience with ML pipeline orchestration tools (e.g., MLflow, Kubeflow, Airflow, Metaflow)
Programming skills in Python (with exposure to ML libraries like TensorFlow, PyTorch)
Experience with cluster administration and Linux
Willingness to learn

What the job involves

We are currently searching for a Machine Learning DevOps with experience in cloud and compute cluster management and Linux administration
Our development and production environment is in the cloud, using several major cloud providers. We need support in managing and automating the processes, and scaling the infrastructure to growing team and production needs
Optimize infrastructure for ML training and inference (e.g., GPUs, distributed compute)
Automate and maintaining ML pipelines (data ingestion, training, validation, deployment)
Manage model versioning, reproducibility, and traceability
Work with terabyte-large datasets
Implement ML-centric CI/CD practices
Monitor model performance and data drift in production
Collaborate with machine learning engineers, software engineers, and platform teams
The role focuses on operationalizing machine learning models, ensuring scalability, reliability, and automation across the ML lifecycle
Intellectually stimulating work environment. Be a pioneer: you get to work with realtime data processing & AI
Work in one of the hottest AI startups, with exciting career prospects. Team members are distributed across the world
Responsibilities and ability to make significant contribution to the company’ success
Inclusive workplace culture

Our take

Machine learning has immense implications for reporting when used on data held by a company, but despite its speed, accuracy and thoroughness it can't currently be applied to incoming data. Put simply, the infrastructure to make this possible is missing, and without this, it's impossible to analyse data in real-time.

Pathway seeks to fix this, providing a streaming data processing layer which is capable of transforming complex, raw events data streams in real-time, allowing enterprises to derive insights in real-time. Reducing latency by over 900x compared to traditional means of data cleansing and transformation, it is currently used in logistics operations by companies such as DB Schenker and La Poste but has applications in financial fraud detection, marketing and IoT usage tracking, among many others.

Founded by women, the company is something of a rarity in the male-dominated European deep tech space, and the Pathway's founders are something of a role model for female engineers. This has only strengthened the founders' resolve to succeed, and with an innovative product meeting a pressing business need, Pathway is poised to achieve this.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (2 rounds)

Nov 2024

$10m

SEED

Dec 2022

$4.5m

SEED

Total funding: $14.5m

Company benefits

Intellectually stimulating work environment. Be a pioneer: you get to work with a new type of data processing framework
Work in one of the hottest data/AI startups in France, with exciting career prospects
Responsibilities and ability to make significant contribution to the company’ success
Inclusive workplace culture

Company HQ

Clichy, France

Leadership

Zuzanna Stamirowska

(CEO)

Previously Co-Chair of the Logistics and Supply Chain Working Group for AIOTI, a spin-off of the European Commission. Before that, they were a PhD Researcher at Université Panthéon-Sorbonne and a Senior Sales Manager for Sphere Research Labs.

Claire Nouet

(COO)

Previously an Analyst at Veolia, a Parliamentary Assistant for the French National Assembly, and a Legal Assistant with Thales.

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