AI Engineers
Listed on 2026-07-01
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IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
AI Engineer
Accellor is an AI-native services firm purpose-built for the post-ChatGPT era. Free from legacy constraints, we focus on delivering measurable business outcomes through advanced AI, data, and engineering capabilities. Our mission is to operationalize AI at scale and unlock sustained enterprise value.
Our offerings span AI solutions, data services, enterprise applications, and product engineering, tailored to industry-specific needs across healthcare, life sciences, telecom, retail, financial services, and technology. By leveraging design thinking and technology-agnostic architectures, we ensure faster time-to-value and seamless interoperability.
With a proven track record of enabling Fortune 100 enterprises and global innovators, Accellor stands as a trusted partner for organizations seeking to harness the full potential of AI. Our vision is clear: to build intelligent, connected ecosystems that deliver measurable outcomes and redefine the future of enterprise transformation.
We're looking to hire strong AI Engineers (multiple roles) with a passion for engineering to join our Product team to help us scale our platform and deliver cutting edge capabilities to our customers.
We are looking for a highly motivated and skilled Generative AI (GenAI) Developers to join our dynamic team. You will be responsible for building and deploying GenAI solutions using large language models (LLMs) to address real-world business challenges. The role involves working with cross-functional teams, applying prompt engineering and fine-tuning techniques, and building scalable AI-driven applications. A strong foundation in machine learning, NLP, and a passion for emerging GenAI technologies is essential.
Responsibilities
- Design, develop, and implement GenAI solutions using large language models (LLMs) to address specific business needs using Python.
- Collaborate with stakeholders to identify opportunities for GenAI integration and translate requirements into scalable solutions.
- Preprocess and analyze unstructured data (text, documents, etc.) for model training, fine-tuning, and evaluation.
- Apply prompt engineering, fine-tuning, and RAG (Retrieval-Augmented Generation) techniques to optimize LLM outputs.
- Deploy GenAI models and APIs into production environments, ensuring performance, scalability, and reliability.
- Monitor and maintain deployed solutions, incorporating improvements based on feedback and real-world usage.
- Stay up to date with the latest advancements in GenAI, LLMs, and orchestration tools (e.g., Lang Chain, Llama Index).
- Write clean, maintainable, and well-documented code, and contribute to team-wide code reviews and best practices.
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