Applied AI Engineer

The role

Applied AI Engineers work forward deployed with customers to lead the end-to-end delivery of technical solutions. You will design and deploy systems leveraging Generative AI, Computer Vision, and Machine Learning.

What you will do

• Engage with enterprise and strategic customers to understand workflows, data, and technical requirements.
• Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models.
• Lead full project lifecycles including scoping, design, development, implementation, testing, deployment, and iteration.
• Integrate and optimize AI/ML pipelines including data preprocessing, prompt engineering, model selection, and evaluation.
• Build reliable, scalable software integrations using APIs, cloud services, and containerized systems.
• Troubleshoot complex technical issues across applications, models, data pipelines, infrastructure, and integrations.
• Act as the customer's trusted technical advisor to enable adoption of product capabilities.
• Partner with internal product and engineering teams to communicate customer feedback.
• Produce high-quality documentation, architecture diagrams, runbooks, and technical assets.
• Mentor junior engineers and contribute to internal best practices.

Required qualifications

• 5–10+ years in engineering roles such as Forward Deployed Engineer, ML Engineer, Software Engineer, Solutions Engineer, Technical Consultant, or similar.
• Strong proficiency in Python, JavaScript/TypeScript, Go, or similar production-oriented languages.
• Hands-on experience with Machine Learning, including training, fine-tuning, evaluating, or deploying models.
• Direct experience with Generative AI (LLMs, multimodal models) and applying them to real-world problems.
• Exposure to Computer Vision techniques (detection, segmentation, OCR, embeddings, multimodal pipelines).
• Strong knowledge of ML frameworks (PyTorch, TensorFlow, OpenCV, etc.).
• Experience with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Excellent communication skills with both technical and non-technical audiences.
• Comfort leading customer-facing engagements and guiding stakeholders through ambiguity.
• Willingness and ability to travel frequently.

Nice to have

• Prior experience in consulting, technical solutions, professional services, or customer-embedded technical roles.
• Experience with vector databases, embedding pipelines, or retrieval-augmented generation (RAG).
• Experience building APIs, microservices, or distributed systems.
• Familiarity with MLOps tools (Docker, Kubernetes, model registries, CI/CD for ML).
• Background in deploying or fine-tuning CV models (YOLO, SAM, CLIP, DETR, etc.).
• Experience in startup or high-growth environments.

Benefits

• Innovative Environment
• Collaborative Culture
• Professional Growth
• Competitive Compensation including salary and equity package

About the company

Nexxa.ai is building artificial super intelligence for heavy industries. The mission is to translate deep technical breakthroughs into operational reality for manufacturing, large-scale infrastructure, logistics and legacy environments.