Deep learning architectures (CNNs, transformers) jobs

Design, develop, and build secure and scalable back‑end systems for Apple Ads Machine Learning Platform, enabling Ads teams to improve and scale ML features, models, and applications.

Responsibilities

Design and develop secure and scalable back‑end systems
Build high‑performing, elegant systems from the ground up
Select technologies and build right solutions for ad network challenges
Build machine learning products that deliver on privacy commitments

Requirements

MS in Computer Science or related field
BS in Computer Science or related field
Nice to have: prior experience applying ML at scale in advertising
Nice to have: recommender systems
Nice to have: information retrieval

Skills

deep learning architectures training frameworks such as PyTorch or TensorFlow ML lifecycle: training, evaluation, deployment and serving distributed training low‑latency serving

Applied AI Engineer

Mindlance · Posted Nov 12, 2026

Open

McLean, Virginia, United States
On-site
Contract · Mid
2–4 years

Apply with RefersoAI Apply on careers page

Design, develop, and deploy advanced AI models and intelligent systems, focusing on GenAI solutions and enterprise integration.

Responsibilities

Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications
Develop and evaluate LLMs
Design and deploy systems using vector databases and knowledge bases
Curate enterprise data with connectors integrated into AWS Bedrock Knowledge Base/Elastic
Implement Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication

Requirements

Bachelor’s degree in Computer Science, Data Science, AI/ML, or related technical field
Nice to have: containerization and orchestration technologies (Docker, Podman, Kubernetes)
Nice to have: experience in financial accounting, fixed income, and capital market
Nice to have: ML Ops tools

Skills

shell scripting python perl Apache Spark AWS Bedrock AWS cloud platforms

AI Tech Lead

Steampunk · Posted Nov 12, 2026

Open

McLean, Virginia, United States
On-site
Full-time · Lead
$140K–$180K per year
8+ years

Apply with RefersoAI Apply on careers page

Develop enterprise grade predictive and generative AI solutions, applications, pipelines, visualizations, and more, leading and mentoring a team of developers.

Compensation

The projected compensation range for this position is $140,000 to $180,000. The estimate displayed represents a typical annual salary range for this position.

Responsibilities

Lead and mentor a team of developers working on cutting-edge predictive and generative AI solutions
Architect and oversee the development of scalable AI/ML systems
Drive the adoption of AI technologies across the organization
Design and implement end-to-end machine learning pipelines
Establish and enforce best practices for AI development

Requirements

Bachelor's degree

Skills

Python TensorFlow PyTorch scikit-learn Machine Learning Algorithms Deep Learning Architectures Natural Language Processing

Associate Machine Learning Engineer

ImagineArt · Posted Nov 11, 2026

Open

Islamabad
On-site
Full-time · Associate
0–2 years

Apply with RefersoAI Apply on careers page

Build and deploy machine learning models for real‑world AI products, including generative and deep learning systems.

Responsibilities

Develop, train, evaluate, and improve machine learning models
Work with deep learning architectures and modern ML frameworks
Assist in implementing and experimenting with neural networks, transformers, and generative models
Perform data preprocessing, feature engineering, model evaluation, and error analysis
Experiment with different model architectures, training configurations, and hyperparameters

Requirements

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field
Nice to have: Exposure to Generative AI
Nice to have: LLMs
Nice to have: diffusion models
Nice to have: computer vision

Skills

Python PyTorch TensorFlow NumPy Pandas Scikit-learn

Scientifique-chercheur en IA Appliquée /Applied AI Research Scientist

Thales Group · Posted Jul 23, 2026

Open

Montréal, Québec, Canada
Hybrid
Full-time

Apply with RefersoAI Apply on careers page

Scientifique-chercheur en IA Appliquée /Applied AI Research Scientist

Responsibilities

Conduct research in computer vision and AI
Design, adapt and evaluate foundation models
Develop methods for object detection, segmentation, visual reasoning
Conduct pioneering research in frugal learning methods
Establish rigorous evaluation protocols

Requirements

PhD or master’s degree in computer science, electrical engineering, or related field
Nice to have: MLOps
Nice to have: software packaging
Nice to have: SDK development
Nice to have: engineering validation

Skills

Python C++PyTorch Tensorflow Scikit-learn OpenCV deep learning architectures vision-language models

AI Researcher (AV) Internship (PhD Student)

General Motors · Posted Nov 9, 2026

Open

Herzliya, Tel Aviv District, Israel
Hybrid
Internship · Intern

Apply with RefersoAI Apply on careers page

Lead research and prototyping of advanced machine learning methods for autonomous driving.

Responsibilities

Lead research and prototyping of advanced machine learning methods
Prototype ML models that improve perception, prediction, or decision-making for autonomous driving
Collaborate with cross-functional teams
Participate in technical discussions, share insights, and work towards publishing results

Requirements

Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or related technical field
Nice to have: familiarity with autonomous vehicles or advanced driver assistance systems (ADAS)
Nice to have: experience with large-scale datasets and training ML models in high-performance computing environments
Nice to have: grants
Nice to have: patents

Skills

Python PyTorch TensorFlow deep learning architectures transformers generative models

AI Software Engineer

Deloitte · Posted Nov 9, 2026

Open

Haifa, Haifa District, Israel
Hybrid
Full-time · Mid
4+ years

Apply with RefersoAI Apply on careers page

Lead the design and development of LLM-based agentic systems and deliver end-to-end AI solutions on NVIDIA GPU platforms.

Responsibilities

Lead the design and development of LLM-based agentic systems.
Own end-to-end delivery of AI solutions, from architecture and prototyping to production deployment using rigorous software engineering practices.
Optimize model performance, latency, and throughput on NVIDIA GPU platforms.
Design clean, maintainable, and scalable software architectures.
Collaborate with customers, product teams, and engineers to translate requirements into technical solutions.

Requirements

BSc or MSc in Computer Science, Electrical Engineering, or a related field
Nice to have: NVIDIA technologies
Nice to have: GPU performance profiling and optimization
Nice to have: high-performance or low-latency systems
Nice to have: Multimodal LLM agents for text, image, audio, and video processing

Skills

Python modern AI frameworks Large Language Models (LLMs)CUDA