nexxa - Forward Deployed Engineer
Requirements
• 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. • 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. • A customer-obsessed senior engineer who thrives in deeply technical, fast-moving environments. • A creative problem solver who can translate vague requirements into robust, scalable solutions. • Someone excited to combine software engineering with real-world AI deployments. • A leader who can own outcomes end-to-end and influence both customer and internal teams.
Responsibilities
• Engage directly with enterprise and strategic customers to understand their workflows, data, and technical requirements. • Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models, and customer data sources. • Lead full project lifecycles: scoping, solution 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 the stack—applications, models, data pipelines, infrastructure, and integrations. • Act as the customer’s trusted technical advisor, enabling adoption of new product capabilities and AI features. • Partner closely with internal product and engineering teams to communicate customer feedback and shape roadmap direction. • Produce high-quality documentation, architecture diagrams, runbooks, and technical assets for customer teams. • Mentor junior engineers and contribute to internal best practices for FDE delivery.
Benefits
• Innovative Environment: Play a critical role in transforming heavy industries through groundbreaking AI and automation technologies. • Collaborative Culture: Be part of a team that values innovation, discipline, and continuous improvement. • Professional Growth: Benefit from significant opportunities for career development and advancement. • Competitive Compensation: Enjoy a comprehensive salary and equity package reflective of your expertise and contributions. • If you're passionate about development and eager to shape the infrastructure powering advanced AI solutions, we'd love to connect.
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