The Role
Develops and deploys enterprise AI solutions, especially LLM and VLM applications, TTS, STT, and machine learning models. Responsibilities include model research, training, fine-tuning, evaluation, optimization, API and microservice integration, production deployment, monitoring, MLOps, CI/CD, security, scalability, and cost optimization. The role requires close collaboration with data engineers, DevOps, product teams, project managers, and clients to deliver reliable, production-ready AI systems.
Summary Generated by Built In
As an AI/ML Engineer at vector8, you will 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 the model performance, and contributing to enterprise-grade reliability, security, and scalability.
This is a hands-on engineering role where you will:
You will work closely with vector8’s Engineers and Project Managers to co-design AI foundations that enable organizations to scale AI from individual use cases to enterprise-wide capabilities.
The role is primarily based in Paris, with occasional travel to client sites and collaboration with teams across Europe.
Job requirements
Job responsibilities
1. End-to-End Model Development
Benefits
Why This Role is Unique
This is a hands-on engineering role where you will:
- 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)
- Contribute to solving real-world enterprise challenges (security, compliance, legacy system integration)
- Participate in the full lifecycle of AI models, from data exploration to production monitoring
You will work closely with vector8’s Engineers and Project Managers to co-design AI foundations that enable organizations to scale AI from individual use cases to enterprise-wide capabilities.
The role is primarily based in Paris, with occasional travel to client sites and collaboration with teams across Europe.
Job requirements
- 3–5 years of experience in AI/ML engineering, software development, or a related field
- Working knowledge of LLM architectures and training methodologies: Transformers, attention mechanisms, fine-tuning, RAG, quantization, Prompt engineering, model evaluation, bias detection
- Solid understanding of machine learning architectures: fully connected, CNN, LSTM, transformers and classical ML models
- Good software engineering skills:
- Proficiency in Python (FastAPI, Pydantic, asyncio, type hints)
- Experience with API development
- Familiarity with modern toolchains (Docker, Kubernetes, Terraform)
- Practical experience with LLM integrations: LLM providers; Vector databases (Pinecone, Weaviate, Milvus); Model serving (vLLM, TGI, KServe)
- Some exposure to MLOps and production deployments
- Understanding of enterprise considerations: security, compliance, scalability, cost optimization.
- Experience with relational and non-relational databases.
- Strong problem-solving and debugging skills.
- Good communication and collaboration skills (fluent in English; French or German is a plus).
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field.
- Exposure to multi-cloud environments (AWS, Azure, GCP) is advantageous.
- Familiarity with code optimisation techniques (e.g., model quantization, parallelization) is a plus.
Job responsibilities
1. End-to-End Model Development
- Implement and deploy distributed, high-volume, high-performance, low-latency machine learning solutions, with a focus on GenAI models, and especially LLM integrations and API-driven architectures
- Contribute to model lifecycle activities:
- Data exploration and cleaning to build reproducible, versioned datasets
- Research to identify appropriate architectures for the problem (e.g., transformers, RAG, fine-tuning)
- Implementation, training, and optimization in reproducible environments
- Deployment, monitoring, and maintenance in production
- Optimize models for performance, latency, and cost efficiency, especially in LLM serving and inference
- Write clean, modular, and well-documented code in Python (FastAPI, Pydantic, asyncio)
- Apply best practices in: 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
- Implement AI-powered solutions that integrate with APIs, microservices, and event-driven architectures
- Develop and contribute to AI pipelines for: Dataset cleaning, preprocessing and model training; Fine-tuning (domain adaptation, instruction tuning); Retrieval-Augmented Generation (RAG) (vector databases, semantic search); Prompt engineering (optimizing inputs 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 and optimize performance (latency, throughput, token efficiency for Transformer based architectures)
- Deploy and monitor AI models in production
- Contribute to MLOps pipelines for: Model training, fine-tuning, and evaluation; Model versioning and lineage tracking; A/B testing and canary deployments
- Support 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, and quality assurance in an agile, cross-functional team
- Share knowledge and promote best practices in AI/ML and software engineering
- Translate product requirements into technical solutions
- Document architectures, decisions, and best practices for internal and client-facing use
- Develop relationships with internal and external stakeholders, including clients and partners
- Stay current with the latest AI and ML architectures (transformers, Mixture of Experts, sparse attention).
- Experiment with emerging 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).
Benefits
- A great compensation package with competitive benefits, including:
- Flexible working hours, including remote work options (hybrid model).
- 25 days of paid vacation per year, plus additional flex 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 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.
- 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.
Skills Required
- 3-5 years of experience in AI/ML engineering, software development, or a related field
- Working knowledge of LLM architectures and training methodologies, including Transformers, attention mechanisms, fine-tuning, RAG, quantization, prompt engineering, model evaluation, and bias detection
- Understanding of machine learning architectures including fully connected networks, CNNs, LSTMs, Transformers, and classical machine learning models
- Proficiency in Python, including FastAPI, Pydantic, asyncio, and type hints
- Experience with API development
- Familiarity with Docker, Kubernetes, and Terraform
- Experience integrating LLM providers, vector databases, and model-serving platforms
- Some exposure to MLOps and production deployments
- Understanding of enterprise security, compliance, scalability, and cost optimization
- Experience with relational and non-relational databases
- Strong problem-solving and debugging skills
- Good communication and collaboration skills
- Fluency in English
- Bachelor's or Master's degree in Computer Science, Mathematics, Physics, or a related field
- French or German language skills
- Exposure to AWS, Azure, or GCP multi-cloud environments
- Familiarity with code optimization techniques such as model quantization and parallelization
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The Company
What We Do
vector8 is an enterprise AI transformation partner that helps ambitious organisations adopt and use artificial intelligence. It advises clients on the best path forward and builds tailored solutions that create competitive advantage. The company combines human expertise with advanced AI technologies to improve growth, efficiency and resilience, while its engineers, consultants and innovators deliver practical solutions across sectors for global clients.
