AI Specialist
Systems Plus Transformations · Job, Auvergne-Rhône-Alpes, France
- On site
- Full-time
- $150,000 / year
- Job, Auvergne-Rhône-Alpes, France
Job highlights
- Develop advanced AI models and autonomous agents.
- Implement cutting-edge vector databases and search solutions.
- Work with generative AI, text-to-video, and multimodal models.
- Leverage AWS for AI model deployment and scaling.
- Apply MLOps and security best practices to AI systems.
About the role
AI Specialist
Systems Plus Transformations is seeking an experienced AI Specialist for a remote position. This role involves designing, training, and optimizing AI/ML models across various domains including Natural Language Processing (NLP), computer vision, and generative AI. You will develop autonomous AI agents capable of complex decision-making and real-time data processing. A key focus will be on implementing and optimizing vector search solutions using technologies like FAISS, Pinecone, Weaviate, or Milvus for advanced AI-powered search and retrieval. The position also includes working on cutting-edge text-to-video generation, speech synthesis, and multimodal AI applications.
Key Responsibilities:
- Design, train, and optimize AI/ML models for NLP, computer vision, and generative AI.
- Develop autonomous AI agents for decision-making and real-time data processing.
- Implement and optimize vector search solutions (FAISS, Pinecone, Weaviate, Milvus).
- Work on text-to-video generation, speech synthesis, and multimodal AI.
- Deploy and manage AI models on AWS infrastructure (SageMaker, Bedrock, Lambda, etc.).
- Ensure efficient AI model inference, distributed computing, and GPU acceleration.
- Build and maintain data pipelines for AI/ML workloads.
- Automate AI model training, deployment, and monitoring using MLOps practices.
- Implement best practices for AI model security, data governance, and responsible AI.
- Collaborate with software and data engineers to integrate AI solutions.
Requirements:
- 8+ years of experience in AI/ML development and deployment.
- Expertise in Python with frameworks like PyTorch, TensorFlow, Hugging Face, LangChain, OpenAI APIs.
- Strong experience with AWS AI/ML services (SageMaker, Bedrock, Lambda, etc.).
- Hands-on expertise in vector databases (FAISS, Pinecone, Weaviate, Milvus).
- Experience developing AI Agents (LangChain, AutoGPT, RAG).
- Familiarity with text-to-video AI tools (RunwayML, Pika Labs, Stability AI).
- Deep knowledge of LLM fine-tuning, prompt engineering, and RAG.
- Proficiency in MLOps best practices (CI/CD, model monitoring).
- Experience with real-time AI workloads (Kafka, AWS Kinesis).
- Strong background in distributed computing and GPU acceleration (CUDA, AWS Inferentia).
Preferred Qualifications:
- Experience with reinforcement learning (RLHF), autonomous agents, and decision-making AI.
- Knowledge of synthetic data generation.
- Understanding of AI model compression techniques.
- Experience in multi-modal AI models.
Preferred Skills:
- Reinforcement Learning, Generative AI, or Explainable AI (XAI).
- Vector Databases, RAG, and AI model optimization.
- GPU acceleration, CUDA, and edge AI deployment.
- AI ethics, bias mitigation, and regulatory compliance.
Key skills/competency:
- AI Model Development
- AI Agents & Automation
- Vector Databases & AI Search
- Text-to-Video & Generative AI
- AWS AI/ML
- MLOps
- Python (PyTorch, TensorFlow)
- LLM Fine-tuning & Prompt Engineering
- Distributed Computing & GPU Acceleration
- Responsible AI & Security
Skills & topics
- AI Specialist
- Artificial Intelligence
- Machine Learning
- NLP
- Computer Vision
- Generative AI
- AI Agents
- Vector Databases
- Text-to-Video
- AWS
- SageMaker
- PyTorch
- TensorFlow
- LangChain
- MLOps
How to get hired
- Tailor your resume: Highlight your 8+ years of AI/ML experience, Python expertise (PyTorch, TensorFlow, LangChain), and specific AWS AI/ML services used, aligning them with the job description's requirements.
- Showcase relevant projects: Emphasize your experience with vector databases (FAISS, Pinecone), AI agents (LangChain, RAG), and generative AI tools, including any text-to-video or multimodal projects.
- Quantify achievements: Use data to demonstrate the impact of your AI model development and deployment efforts, particularly in areas like optimization, scalability, and automation via MLOps.
- Prepare for technical interviews: Be ready to discuss your in-depth knowledge of LLM fine-tuning, prompt engineering, RAG, distributed computing, and GPU acceleration (CUDA, AWS Inferentia).
- Demonstrate cloud proficiency: Highlight your practical experience with AWS AI/ML services such as SageMaker, Bedrock, Lambda, and Step Functions, along with MLOps tools like Terraform and GitHub Actions.
Technical preparation
Master Python libraries: PyTorch, TensorFlow, Hugging Face, LangChain.,Deep dive into AWS AI/ML services: SageMaker, Bedrock, Lambda.,Practice with vector databases: FAISS, Pinecone, Weaviate, Milvus.,Build AI agents using RAG and OpenAI APIs.
Behavioral questions
Describe a complex AI model you developed and deployed.,How do you ensure AI model security and compliance?,Explain your experience collaborating with cross-functional teams.,How do you stay updated with AI advancements?
Frequently asked questions
- What are the core responsibilities for an AI Specialist at Systems Plus Transformations?
- The AI Specialist role at Systems Plus Transformations focuses on designing, training, and deploying advanced AI/ML models, including those for NLP, computer vision, and generative AI. Key responsibilities include developing AI agents, implementing vector databases for search, working with text-to-video generation, deploying models on AWS, and ensuring model scalability and security.
- What specific AI technologies and tools are crucial for this AI Specialist position?
- This role requires expertise in Python with libraries like PyTorch, TensorFlow, Hugging Face, LangChain, and OpenAI APIs. Proficiency in AWS AI/ML services (SageMaker, Bedrock), vector databases (FAISS, Pinecone), AI agent frameworks (LangChain, RAG), and MLOps practices are essential.
- How much experience is required for the AI Specialist role at Systems Plus Transformations?
- Systems Plus Transformations is looking for candidates with a minimum of 8 years of experience in AI/ML development, specifically focusing on building and deploying AI-powered applications. This includes hands-on experience with various AI technologies and cloud platforms.
- Is this AI Specialist position remote, and what are the implications for candidates?
- Yes, this AI Specialist position is fully remote. This means you can work from any location, but you should be prepared for remote collaboration and potentially asynchronous communication depending on team structures.
- What are the preferred qualifications for an AI Specialist at Systems Plus Transformations?
- Preferred qualifications include experience with reinforcement learning (RLHF), autonomous agents, decision-making AI, synthetic data generation, AI model compression, and multi-modal AI models integrating text, video, and speech.
- How does Systems Plus Transformations approach MLOps and cloud infrastructure for AI?
- Systems Plus Transformations emphasizes robust MLOps practices for automating AI model training, deployment, and monitoring using tools like AWS SageMaker Pipelines, Terraform, Docker, and GitHub Actions. They leverage AWS cloud infrastructure extensively for deploying and managing AI models.
- What kind of AI projects can I expect to work on as an AI Specialist at Systems Plus Transformations?
- You can expect to work on a diverse range of AI projects, including advanced AI model development, creating autonomous AI agents, implementing sophisticated AI-powered search systems using vector databases, and developing generative AI applications like text-to-video and speech synthesis.