Senior AI/ML Engineer, France

As a Senior AI/ML Engineer at vector8, you will design, implement, and deploy AI solutions that bridge the gap between research and production. Your work will focus on integrating and fine‑tuning AI models, optimizing model performance, and ensuring enterprise‑grade reliability, security, and scalability.

Hands‑on Engineering Role

Develop and optimize LLM and VLM‑powered solutions for enterprise use cases

Develop and optimize TTS, 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 toolchains (Docker, Kubernetes, Terraform)

Hands‑on experience with LLM integrations:

LLM providers

Vector databases (Pinecone, Weaviate, Milvus)

Model serving (vLLM, TGI, KServe)

Experience with MLOps and production deployments

Understanding of enterprise challenges:

Security, compliance, scalability, cost optimization

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)

Job Responsibilities

End‑to‑end model development

Design, implement, and deploy distributed, high-volume, high‑performance, low‑latency machine‑learning solutions, focusing on GenAI models, especially LLM integrations and API‑driven architectures

Take ownership of models throughout their lifecycle: data exploration and cleaning, reproducible, versioned datasets, state‑of‑the‑art research to identify best architectures, implementation, training, optimization, deployment, monitoring, maintenance, and optimization for performance, latency, and cost efficiency in LLM serving and inference

Write clean, modular, well‑documented Python code (FastAPI, Pydantic, asyncio)

Apply best practices: testing (unit, integration, end‑to‑end), CI/CD (GitHub Actions, GitLab CI, ArgoCD), observability (logging, monitoring, tracing)

Ensure security and compliance: data protection, access controls, encryption

Integrate models and code into CI/CD pipelines for seamless deployment

Design and implement AI‑powered solutions that integrate with APIs, microservices, and event‑driven architectures

Develop and optimize AI pipelines for dataset cleaning, preprocessing, and model training; fine‑tuning; retrieval‑augmented generation; prompt engineering

Model evaluation (benchmarking, bias detection, drift analysis)

Build scalable, secure, cost‑efficient serving infrastructure (FastAPI, vLLM)

Debug and optimize performance (latency, throughput, token efficiency for transformer‑based architectures)

Deploy and monitor AI models in production

Design and implement MLOps pipelines: training, fine‑tuning, evaluation, versioning and lineage tracking, A/B testing, canary deployments

Ensure scalability and reliability (auto‑scaling, fault tolerance, disaster recovery)

Collaborate with data engineers to build data pipelines (batch, streaming, real‑time)

Work closely with product owners, DevOps, QA 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

Stay ahead of the latest AI and ML architectures (transformers, Mixture of Experts, sparse attention)

Experiment with cutting‑edge techniques (quantization, distillation, speculative decoding)

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

Job Benefits

A competitive compensation package with benefits

Flexible working hours, including remote work options (hybrid model)

25 days of paid vacation per year, plus additional flex days

Private health, life insurance and a pension plan for long‑term security

Home office allowance and lunch vouchers

Discounted fitness memberships

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

Opportunities to attend industry events and represent vector8 as a thought leader

A less‑formal work environment where authenticity and collaboration thrive

A diverse and inclusive team that values curiosity, ownership, and innovation

Why This Role is Unique

You will work at the intersection of AI research and enterprise software engineering with a strong focus on AI‑driven solutions

You will contribute to shaping the future of AI adoption in France’s most complex organizations

You will bridge the gap between cutting‑edge AI and real‑world enterprise constraints (security, compliance, legacy systems)

You will grow your skills, collaborate with talented engineers, and have real ownership over your work from day one

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