Lineal
Machine Learning Engineer/Applied Scientist
Direct message the job poster from Lineal
Human Resources and Talent Acquisition Manager Lineal, an innovative eDiscovery and legal technology services firm, is made up of a team of industry innovators, wary of outdated solutions, who are highly driven and motivated to work together to further Lineal’s promise of countering legal’s most pressing issues through an optimal blend of advanced technologies.
We’re looking for a
Machine Learning Engineer
with hands-on experience building and shipping
LLM-powered applications . You’ll join a small, high-impact team developing an
agentic document search and conversational assistant platform
that combines hybrid search (traditional + embeddings + RAG) with multi-turn dialogue, task planning, and data analysis.
What You’ll Do
Design and optimize hybrid search and retrieval systems (RAG, embeddings, semantic ranking).
Build conversational agents with memory, context retention, and task orchestration.
Enable structured data querying, analysis, and automated visualizations.
Collaborate with engineering and DevOps to deploy in Kubernetes-based environments.
Contribute to architecture decisions on LLM orchestration, retrieval strategies, and system design.
What We’re Looking For
Proven track record shipping
LLM-based applications
to production.
Strong experience with retrieval systems (vector search, RAG, hybrid pipelines).
Familiarity with multi-turn conversational agents and agentic AI workflows.
Practical experience with Python LLM tools (LangChain, LangGraph, etc.) and cloud-hosted APIs (OpenAI, Anthropic).
Solid ML/NLP foundation, including transformers and earlier approaches (BERT, LSTMs, Word2Vec, etc.).
Comfortable in small, cross-functional teams and Kubernetes-based deployments.
Nice-to-Have
Startup or small-team experience.
Experience in regulated or high-stakes industries.
Seniority level Associate
Employment type Full-time
Job function Information Technology
Industries Legal Services
#J-18808-Ljbffr
Human Resources and Talent Acquisition Manager Lineal, an innovative eDiscovery and legal technology services firm, is made up of a team of industry innovators, wary of outdated solutions, who are highly driven and motivated to work together to further Lineal’s promise of countering legal’s most pressing issues through an optimal blend of advanced technologies.
We’re looking for a
Machine Learning Engineer
with hands-on experience building and shipping
LLM-powered applications . You’ll join a small, high-impact team developing an
agentic document search and conversational assistant platform
that combines hybrid search (traditional + embeddings + RAG) with multi-turn dialogue, task planning, and data analysis.
What You’ll Do
Design and optimize hybrid search and retrieval systems (RAG, embeddings, semantic ranking).
Build conversational agents with memory, context retention, and task orchestration.
Enable structured data querying, analysis, and automated visualizations.
Collaborate with engineering and DevOps to deploy in Kubernetes-based environments.
Contribute to architecture decisions on LLM orchestration, retrieval strategies, and system design.
What We’re Looking For
Proven track record shipping
LLM-based applications
to production.
Strong experience with retrieval systems (vector search, RAG, hybrid pipelines).
Familiarity with multi-turn conversational agents and agentic AI workflows.
Practical experience with Python LLM tools (LangChain, LangGraph, etc.) and cloud-hosted APIs (OpenAI, Anthropic).
Solid ML/NLP foundation, including transformers and earlier approaches (BERT, LSTMs, Word2Vec, etc.).
Comfortable in small, cross-functional teams and Kubernetes-based deployments.
Nice-to-Have
Startup or small-team experience.
Experience in regulated or high-stakes industries.
Seniority level Associate
Employment type Full-time
Job function Information Technology
Industries Legal Services
#J-18808-Ljbffr