Lead R&D Engineer; NLP​/LLM

Position: Lead R&D Engineer (NLP/LLM) Soft Serve is a global digital solutions company, headquartered in Austin, Texas, founded in 1993. Our associates work on 2,000+ projects with clients in the USA, Europe, LATAM, and APAC. We are about people who create bold things, make a difference, have fun, and love their work. Our team significantly contributes to innovative research and development projects at the intersection of science, engineering, and creativity. We aim at designing transformative AI solutions that impact various application domains IF YOU ARE • An expert with 7+ years of hands-on experience in AI/ML, including 3+ years leading R&D and production-ready projects • Holding a PhD or Master’s in Machine Learning, Computer Science, or related fields, or equivalent senior industry experience • A recognized specialist in NLP and LLMs, with experience in training, fine-tuning, retrieval-augmented generation (RAG), and large-scale evaluation • Experienced in designing and deploying Agentic AI systems, including multi-agent orchestration, tool integrations, and autonomous workflows • Highly proficient in Python, with additional skills in C++/Java for optimizing performance-critical components • Deeply familiar with PyTorch, Hugging Face Transformers, Lang Chain, Llama Index, and related NLP/LLM frameworks • Skilled in working with vector databases and retrieval systems for real-time knowledge grounding in AI agents • Experienced in cloud architectures (AWS, GCP, Azure) and distributed training for large models, including quantization and fine-tuning for deployment efficiency • Knowledgeable in MLOps practices, including bolthires/CD pipelines for ML, Docker/Kubernetes orchestration, and monitoring/model lifecycle management • A leader who can mentor cross-functional ML/AI teams and align research with organizational priorities • Confident in presenting complex AI/ML concepts to executives, product managers, or external stakeholders in clear and understandable form • The obe who has published in or contributed to research, patents, or open-source projects in NLP, LLMs, reinforcement learning, or multi-agent AI systems • Aware of and committed to AI ethics, fairness, bias mitigation, and data security within generative and agentic AI applications AND YOU WANT TO • Define and execute the R&D roadmap for advanced NLP, LLM, and Agentic AI systems • Lead the development of novel architectures for multi-agent orchestration, tool-use integration, and retrieval-augmented generation • Drive collaboration with product, engineering, and research teams to align AI innovation with business impact • Architect scalable training, fine-tuning, and deployment workflows on cloud and distributed systems • Establish best practices in MLOps, model evaluation, and responsible AI for production-grade deployments • Mentor and grow a high-performing team of AI engineers and researchers • Communicate progress, technical insights, and breakthroughs to executives and stakeholders TOGETHER WE WILL • Be Game Changers who represent our best talent, top contributors, and creative minds in the annual Soft Serve Awards • Work with a diverse team of professionals in a collaborative enterprise environment • Create an exceptional customer experience, impact the company's global success, and be recognized by the Customer Hero Program • Boost leadership skills with managerial competencies through leadership development programs that enable emerging and mature leaders to deliver more value • Gain performance-based bonuses and incentives Soft Serve is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, age, sex, nationality, disability, sexual orientation, gender identity and expression, veteran status, and other protected characteristics under applicable law. Let’s put your talents and experience in motion with Soft Serve. SOFTSERVE IS WHERE YOU ARE Enjoy our Flexible Workplace - work from home, or in any office of your country! #J-18808-Ljbffr Apply tot his job Apply tot his job