Senior AI/ML Engineer, France
Indexed description
This Is a Hands-on Engineering Role Where You Will
- Develop andoptimizeLLMand VLM-powered solutions for enterprise use cases
- Develop andoptimizeTTS, STT and ML models.
- Apply software engineering best practices (testing, CI/CD, modular design, documentation)
- Collaborate with cross-functional teams (data engineers,MLOps, cloud architects, and business stakeholders)
- Solve real-world enterprise challenges (security, compliance, legacy system integration)
- Own the full lifecycle of AI models, from data exploration to production monitoring
The role is primarily based in Paris, with occasional travel to client sites and collaboration with teams across Europe.
Job Requirements
- 5+ years of experience in AI/ML engineering, software development, or a related field
- Expertise in LLM architectures and training methodologies:
- Transformers, attention mechanisms, fine-tuning, RAG, quantization
- Prompt engineering, model evaluation, bias detection
- Strong knowledge of machine learning architectures: fully connected, CNN, LSTM, transformers and classical ML models
- Strong software engineering skills:
- Proficient in Python (FastAPI,Pydantic,asyncio, type hints)
- Experience with API development
- Familiarity with modern tool chains (Docker, Kubernetes, Terraform)
- Hands-on experience with LLM integrations:
- LLM providers
- Vector databases (Pinecone, Weaviate, Milvus)
- Model serving (vLLM, TGI, KServe)
- Experience with MLOpsand production deployments
- Understanding of enterprise challenges:
- Security, compliance, scalability, costoptimization.
- Experience with relational and non-relational databases.
- Strong problem-solving and debugging skills.
- Excellent communication and collaboration skills (fluent in English; German is a strong plus).
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field.
- Experience with multi-cloud environments (AWS, Azure, GCP).
- Experience with code optimization (e.g., model quantization, parallelization).
- Testing (unit, integration, end-to-end)
- CI/CD (GitHub Actions, GitLab CI,ArgoCD)
- Observability (logging, monitoring, tracing)
- Dataset cleaning,preprocessingand model training
- Fine-tuning (domain adaptation, instruction tuning)
- Retrieval-Augmented Generation (RAG) (vector databases, semantic search)
- Prompt engineering (optimizinginputs for performance, cost, and accuracy)
- Model evaluation (benchmarking, bias detection, drift analysis)
- Build scalable, secure, and cost-efficient serving infrastructure (e.g.,FastAPI,vLLM)
- Debug andoptimizeperformance (latency, throughput, token efficiencyfor Transformer based architectures)
- Enterprise AI & MLOps
- Deploy andmonitorAI models in production
- Design and implementMLOpspipelines for:
- Model training, fine-tuning, and evaluation
- Model versioning and lineage tracking
- A/B testing and canary deployments
- Ensure scalability and reliability (auto-scaling, fault tolerance, disaster recovery)
- Collaborate with data engineers to build data pipelines (batch, streaming, real-time)
- Collaboration & Technical Leadership
- Work closely with product owners, DevOps, and quality assurance in an agile, cross-functional team
- Mentor junior engineers and promote best practices in AI/ML and software engineering
- Translate product requirements into technical solutions and architectural decisions
- Document architectures, decisions, and best practices for internal and client-facing use
- Develop relationships with internal and external stakeholders, including clients and partners
- Innovation & Continuous Improvement
- Stay ahead of the latestAI and MLarchitectures (transformers, Mixture of Experts, sparse attention).
- Experiment withcutting-edgetechniques (quantization, distillation, speculativedecoding).
- Evaluate and benchmark open-source and proprietary models (Llama, Mistral,Mixtral, GPT-4, Claude).
- Bring your own ideas through vector8’s ideation process.
- Contribute to vector8’s AI accelerators (reusable components for common industry problems).
- Embrace a strategic and continuous improvement mentality to drive innovation.
- A great compensation package with competitive benefits, including:
- Flexible working hours, including remote work options (hybrid model).
- 25daysof paid vacation per year, plusadditionalflex days.
- Private health and life insurance&pension plan for long-term security.
- Home office allowance &Lunch vouchers to enjoy meals on us.
- Discounted fitness memberships to stay active.
- 50% reimbursement of public transport costs.
- Free coffee, fruit, and snacks to keep you fueled.
- Access to the latest technologies(LangDock, Claude Code for developers)
- Grants for training, coaching, and conferences to support your continuous learning.
- Opportunities to attend industry events and representvector8as a thought leader.
- A less-formal work environment where authenticity and collaboration thrive.
- A diverse and inclusive team that values curiosity, ownership, and innovation.
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