Job Title:ย Senior AI Engineer (or Senior Applied AI Engineer / Senior Machine Learning Engineer)ย
Location:ย Barcelona, Spain (hybrid or onsite; some roles offer flexibility)ย
Company Type:ย Tech firm, deep-tech startup, researchย centerย (e.g., BSC-CNS), or multinational (e.g., Keysight, IQVIA, or similar to INTERA Group’s AI acceleration focus)ย
Employment Type:ย Full-time.ย
About the Roleย
We are seeking a Senior AI Engineer to drive the development and deployment ofย cutting-edgeย AI solutions that solve complex real-world problems. You will own end-to-end AI featuresย from model selection and optimization to production integrationย while collaborating with cross-functional teams (product, backend engineers, researchers). In high-tech contexts like edge AI acceleration or low-power embedded systems, the focus may include hardware-aware optimization, real-time inference, and efficient deployment on constrained devices.ย
Key Responsibilities
- Design, implement, and productionize advanced AI/ML models and pipelines (e.g., LLMs, generative AI, agentic systems, computer vision, anomaly detection, or neuromorphic/edge-optimized models).
- Optimize models for performance, latency, cost, privacy, and reliability (e.g., quantization, compression, distillation for edge deployment).
- Build and integrate LLM-powered features (agents, tool-calling, RAG, prompting strategies) using frameworks like LangChain, PyTorch, TensorFlow, or Hugging Face.
- Deploy scalable AI systems in production environments (cloud like GCP/AWS, or edge/hardware platforms), including CI/CD, monitoring, observability, and MLOps practices.
- Evaluate trade-offs between models/techniques (quality vs. speed vs. cost) and ensure safe, reproducible deployments.
- Collaborate with stakeholders to translate business/user needs into technical requirements; mentor junior engineers and establish best practices (code reviews, testing, maintainability).
- Contribute to research-to-production workflows, potentially in domains like AI acceleration, embedded AI, semiconductors, or scientific/engineering applications.
Required Qualifications
- 7+ years of hands-on software engineering experience, with strong production ownership (Python preferred; familiarity with other languages like C++/Rust for embedded/edge a plus).
- Proven track record deploying AI/ML in production (experience with LLMs, deep learning frameworks, APIs like OpenAI/Hugging Face).
- Solid software engineering fundamentals: design patterns, testing, version control, cloud infrastructure (e.g., Docker, Kubernetes, Terraform, FastAPI/REST).
- Experience with MLOps tools, monitoring (e.g., Prometheus), and handling distributed systems or resource-constrained environments.
- Bachelor’s/Master’s/PhD in Computer Science, AI, Engineering, or related quantitative field (advanced degree often preferred for senior roles).
- Strong problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.
Preferred Skills / Nice-to-Haves
- Expertise in edge AI, hardware acceleration (e.g., neuromorphic, RISC-V, low-power inference), or embedded systems.
- Fine-tuning/training large models, prompt engineering, evaluation techniques, or multi-modal AI.
- Domain knowledge in semiconductors, IoT, healthcare, or scientific computing.
- Contributions to open-source AI/ML projects or publications.
- Experience with specific tools: PydanticAI, LangChain, Vertex AI/SageMaker, or real-time/streaming inference.
What We Offer
- Opportunity to work on impactful, innovative AI (e.g., accelerating hardware design or enabling edge intelligence).
- Collaborative environment with cutting-edge tech and events exposure.
- Competitive compensation, professional growth, and work-life balance.
How to Apply Submit your resume, cover letter, and any relevant portfolio/GitHub via the company careers page or LinkedIn.
