Senior AI/ML Engineer, France

vector8; Paris; On-site; EUR 100,000 - 150,000; Full time

Benefits offered by this job

Flexible working hours

Hybrid work options

Private health insurance

Pension plan

Home office allowance

Lunch vouchers

Transport allowance

Training & conference grants

Job summary

vector8 is seeking a Senior AI/ML Engineer to design, implement, and deploy AI solutions that bridge research and production. You will fine‑tune models, optimize performance, and ensure enterprise‑grade reliability and security while collaborating across Europe.

The role is based in Paris with occasional client-site travel, requiring strong English skills and a track record in LLM integrations and production deployments.

Qualifications

• 5+ years in AI/ML engineering or a related field.
• Expertise in LLM architectures and training methodologies.
• Strong software engineering and Python development skills.
• Experience with enterprise security, compliance, and deployment.

Responsibilities

• End-to-end model development from data to production.
• Design, implement, and deploy distributed, high‑volume ML solutions focusing on GenAI.
• Own models through lifecycle: data, training, evaluation, deployment, monitoring.
• Collaborate with data engineers, MLOps, cloud architects, and stakeholders.
• Ensure security, compliance, and scalable, cost-efficient serving.
• Mentor junior engineers and translate requirements into architecture.

Skills

LLM architectures

Training methodologies

Prompt engineering

Model evaluation

Bias detection

Python

API development

Docker/Kubernetes

MLOps

Multi-cloud

Security/compliance

Data bases

English fluency

German knowledge

Education

Bachelor’s or Master’s in CS/Math/Physics

Tools

Pinecone

Weaviate

Milvus

vLLM

KServe

Terraform

GitHub Actions

Job description

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