Senior AI/ML Engineer for a data spaces platform

AI and Machine Learning.

Senior

Upper-Intermediate English

Required Skills

TensorFlow

PyTorch

Azure ML

Nice to Have

AI

ML

ETL

Data Processing

Scikit-learn

Summary

- We are looking for a Senior ML/AI Engineer to work on building a full-cycle data management platform, which will include data ingestion, ETL, data quality, data enrichment, data processing pipelines orchestrated into an "elastic data fabric" and, most importantly, utilizing federated learning.
- Experience with ML models, algorithms model optimization, and distributed training techniques
- Familiarity with Distributed systems, cloud-native design, and hybrid platforms
- Azure Machine Learning will be a plus
- Start: ASAP
- Duration: Long-term

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Project Description

We are looking for a Senior ML/AI Engineer who will work on developing federated learning and AI features with privacy-preserving techniques.

You will work on a platform that automates data ingestion, processing, and sharing with user-friendly, privacy-preserving, and scalable solutions for industrial manufacturing.

The platform will incorporate scalable and dynamic tools for creating and managing data spaces, handling complex data workflows, and ensuring modularity and privacy compliance.

Preliminary Project's Stack:

Backend: Python, Flask/FastAPI, Go
Frontend: ReactJS, Angular.
AI/ML: Azure Machine Learning, Azure Databricks, TensorFlow Federated, PyTorch, and privacy-enhancing techniques.
Cloud and DevOps: Kubernetes, Docker, Azure DevOps, CI/CD Data pipelines on Azure
Data Engineering: Apache NiFi. Kafka Connect, Databricks - on Azure.
Database: Cosmos DB, Postgres/Hyperscale or MySQL/Healwave

*stack may change during the hiring process of qualified specialists in their areas

Responsibilities:

Your primary responsibilities will include integrating contextualization and schema mapping models into real-time workflows, mentoring team members, contributing to system design, and managing AI/ML complexities.

Requirements:

Experience with ML models, algorithms model optimization, and distributed training techniques (federated learning, e.g., FedAvg, secure aggregation).
Familiarity with Distributed systems, cloud-native design, and hybrid platforms
Building custom ML pipelines on Azure ML
TensorFlow, PyTorch, or scikit-learn
Familiar with Data processing

Would be a plus:

Container orchestration on AKS or Azure Arc

How to Apply for Senior AI/ML Engineer for a data spaces platform

Be ready for the next steps:

Create your profile on our website (import from LinkedIn)
20-30-minute screening call
Technical interview feedback
Project Selection (we are looking for the best project for you).

Who can apply:

We work with developers across Europe, LATAM, the U.S. (W-9 form owners), Canada, Asia, Oceania, and the UK.
We do not provide visa assistance, and this cooperation model does not include direct-hire benefits.
We cannot accept applicants from Russia, Belarus, Iran, or North Korea.

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