Tech jobs
Job listings
Machine Learning Engineer, Sales Engineering
Machine Learning Engineer on Apple's Sales Engineering RAD team in Austin, building and deploying production ML/GenAI systems — LLMs/LMMs, RAG pipelines, and agentic workflows — that power Apple's global Channel Sales, working hands-on with Python, PyTorch/TensorFlow, Hugging Face, and cloud infrastructure.
Stage Ingénieur IA & Machine Learning – Données de simulation (F/H)
Six-month R&D internship in Nantes with SII Atlantique (Groupe SII) exploring how simulation-engine data can train, enrich and evaluate AI/ML models: analyzing simulated vs. industrial data, comparing learning strategies, and feeding results into a project demonstrator. Core stack: Python, scikit-learn, TensorFlow/PyTorch.
Stage - Machine Learning for parameters mapping automation f/m - Strategic Student Program
A 6-month internship (starting January 2027) at Siemens Digital Industries Software in Villeurbanne near Lyon: research, prototype, and evaluate machine-learning methods to automate parameter mapping between Teamcenter Simulation and simulation applications, collaborating with an international product development team.
Machine Learning Engineer
Join Copenhagen Energy Trading as our new Machine Learning Engineer Machine learning is becoming an increasingly important part of how we understand energy markets, improve forecasts, and make trading decisions. We are…
Machine Learning Engineer
12-month contract MLOps/DevOps engineer building and running secure AWS cloud platforms for AI, machine learning and data science solutions in a major Australian Government environment. Works with Terraform/CDK IaC, CI/CD pipelines, Docker/Kubernetes (EKS) and supports generative AI and RAG workloads; requires current NV1 clearance and hybrid work.
AI/ML Software Engineer
Hands-on AI/ML engineer building LLM applications, ML-powered product capabilities, data pipelines, and scalable data infrastructure across ASG's portfolio of SaaS companies. Works in Python/R/SQL with a modern data/ML stack (Bedrock, Sagemaker, Vertex AI, Airflow, Spark, Kafka, Databricks, dbt) and advises/enablements OpCo teams. Remote role with $200k-$250k base plus bonus.
AIML - Machine Learning Engineer, Evaluation - Responsible AI and Safety
ML engineer on Apple's HCMI/Responsible AI team in Cambridge, assessing and improving the safety and fairness of Apple Intelligence's generative AI features. Day-to-day involves designing human annotation datasets and safety metrics, building data pipelines, and reporting evaluation findings, using Python and Pandas.
Ingeniero/a en Inteligencia Artificial
¡Prepárate para vivir una nueva etapa con Periferia IT Group! 🌟Si tienes experiencia como Ingeniero/a en Inteligencia Artificial y quieres generar un impacto en el mundo tecnológico, esta es tu oportunidad para unirte…
Ingeniero/a en Inteligencia Artificial
¡Prepárate para vivir una nueva etapa con Periferia IT Group! 🌟Si tienes experiencia como Ingeniero/a en Inteligencia Artificial y quieres generar un impacto en el mundo tecnológico, esta es tu oportunidad para unirte…
Artificial Intelligence/Machine Learning (AI/ML) Engineer
Designs, trains, tests, deploys, and monitors AI/ML models end to end — data pipelines, statistical analysis, test & evaluation, and turning data science prototypes into scalable solutions. Requires 5 years applied ML, an MS/PhD (or equivalent experience), and an active TS/SCI clearance with full-scope polygraph.
Applied Computer Vision Engineer
About the Role SPREEAI builds AI virtual try-on that fashion brands embed in their sites and apps. Every try-on starts with the same question: did we read the person and the garment correctly? This role owns the…
Staff Machine Learning Engineer
Staff Data Scientist leading end-to-end applied ML and data science initiatives—modeling, pipelines, deployment, and monitoring—at a vacation rental company, with deep focus on pricing, demand forecasting, and optimization using Python, SQL, and cloud/ML tooling.
AI/ML Engineer / Machine Learning Engineer
Deploy and run open-source video-generation AI models on a dedicated GPU server: set up CUDA/PyTorch environments, optimize generation speed and VRAM usage, manage generation queues/stability, and expose models through a simple API or Python backend.