United States onlyLucidworks is leading digital transformation for some of the world's biggest retailers, financial services firms, manufacturers, and B2B commerce organizations. We believe that the core to a great digital experience starts with search and browse. Our Deep Learning technology captures user behavior and utilizes machine learning to connect people with the products, content, and information they need. Brands including American Airlines, Lenovo, Red Hat, and Cisco Systems rely on Lucidworks' suite of products to power commerce, customer service, and workplace applications that delight customers and empower employees. Lucidworks believes in the power of diversity and inclusion to help us do our best work. We are an Equal Opportunity employer and welcome talent across a full range of backgrounds, orientation, origin, and identity in an inclusive and non-discriminatory way.
About the Team
The Lucidworks Data Science Engineering team is responsible for developing our cutting-edge agentic search products, owning them from research all the way out to production. In addition, our team works with almost every other team in the company to power the search technologies behind Lucidworks Search at billion-query level scale.
We collaborate with consultants and customers to learn user needs, gather data, design and prototype solutions, as well as validate preliminary results. We continuously explore new AI technologies, and join industry best practices with the latest ideas from academia to turn them into useful products.
Our research areas include embedding models, hybrid search, LLMs, recommender systems, query understanding, classification, all in both text and multimodal forms.
About the Role
As an Associate Machine Learning Engineer, you’ll have the opportunity to apply foundational AI concepts in a hands-on, production environment. In this role, you’ll work on projects that bring theory into practice, contributing to systems that impact real users while receiving feedback and mentorship to support your growth.
You’ll gain experience with areas such as large language models (LLMs), search relevance, and natural language processing (NLP) challenges, while also exploring the applications of generative AI in search and information retrieval. Your work will include implementing algorithms from documentation and examples, modifying and extending existing code, writing tests, and interpreting results with guidance from senior engineers.
This is a highly collaborative role, where you’ll engage with a diverse, distributed team across multiple time zones. You’ll be encouraged to ask questions, share ideas, and learn continuously as you develop your technical and professional skills.
To ensure fairness and efficiency, we kindly ask that all interest in this role be
submitted through the application link rather than direct outreach.
Responsibilities
- Learn and assist in assessing models and understanding model selection for different use cases
- Support experiments and evaluation for search-specific tasks
- Contribute to integrating pre-trained language and embedding models into search, agentic, and recommendation pipelines
- Support the development of automated model training, assessment, and deployment processes
- Contribute to software and tooling that improves automation and service reliability
- Stay current on AI best practices and share learnings with the team
- Participate in design discussions and contribute fresh perspectives
- Collaborate with software team members in a fast-paced Agile environment
- Grow your skills while working effectively with distributed teams
- All other duties as assigned
Skills & Qualifications
- 0-2 years of professional experience OR relevant internship/project experience
- Bachelor's degree in Computer Science, Data Science, Mathematics, or related field (or equivalent experience)
- Strong programming fundamentals in Python
- Familiarity with common data science libraries such as pandas, numpy, and transformers/sentence-transformers
- Basic exposure to large language models through coursework, tutorials, or personal projects
- Basic understanding of PyTorch
- Basic understanding of microservices concepts and containerization (Docker knowledge preferred)
- Eagerness to learn cloud technologies and production AI systems
- Experience with version control (Git) is a plus
- Exposure to LLM fine-tuning techniques (e.g., LoRA, QLoRA) is preferred
- Familiarity with prompt engineering, context design, and LLM evaluation methods
- Personal or academic projects demonstrating AI implementation or LLM usage or contributions to open-source AI projects are a plus
- Acceptable background check
Our Stack
- Python
- PyTorch
- Ray
- Argo
- Vespa
- Solr
- Redis
- Linux
- Docker and Kubernetes
- Google Cloud Platform
Competencies
- Resourceful: able to proactively discover solutions, learn quickly, and adapt in ambiguous environments.
- Collaborative: works well across teams and geographies, with empathy and inclusivity.
- Organized and detail-oriented: comfortable managing dependencies and backlog grooming.
- Customer-obsessed: listens deeply to user pain points and translates them into impactful product features.
- Ability to handle confidential information
Lucidworks believes in the power of diversity and inclusion to help us do our best work. We are an Equal Opportunity employer and welcome talent across a full range of backgrounds, orientation, origin, and identity in an inclusive and non-discriminatory way. Applicants receive consideration based on the relevant talents, skills, and experiences they offer to our company.
Thank you for your interest and we look forward to learning more about you.
Note to third party recruiters:
We appreciate your interest in our job opportunities. However, we kindly request that third-party recruiters and staffing agencies refrain from contacting us regarding these positions. We prefer to work directly with candidates and do not accept unsolicited resumes or candidate referrals from third-party recruiters or agencies. Unsolicited resumes and referrals will become the property of Lucidworks, and no fee will be paid should we hire a candidate whose resume was sent unsolicited.
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