Applied AI Research Engineer- Fully Remote
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AI Summary
Overview
Verbit is expanding its applied AI group in Ukraine and seeking an Applied AI Research Engineer who excels at combining development, data-driven insights, and production engineering to create meaningful impact. The team works across a broad range of domains — ASR, acoustic modeling, NLP and AI pipeliness — adapting state-of-the-art pre-trained models and techniques to solve specific product challenges. This role is an opportunity to be a core contributor with real influence on Verbit's evolving AI capabilities.
This is a remote position and is open to Ukrainian-speaking candidates only.
Status statement
An agile applied AI team looking for a results-oriented Applied AI Research Engineer who thrives on adapting pre-trained models to real product problems across multiple domains.
Key Responsibilities of the Team
Build AI-Powered Features: Implement product features across ASR, NLP domains powered by pre-trained foundation and task-specific models.
Adapt Pre-Trained Models: Match, fine-tune, and orchestrate pre-trained models (ASR, acoustic, LLMs) to specific challenges.
Prompt & Adaptation Engineering: Design, test, and iterate prompts, fine-tuning recipes, and adaptation strategies to achieve desired behaviors from language, and speech models.
RAG & Agentic Workflows: Implement retrieval-based pipelines and chain-of-thought/agentic reasoning flows.
Evaluation Pipelines: Run quantitative and qualitative evaluations (using automation and human feedback) to measure performance, correctness, and UX.
Data Preparation: Work with raw data to structure datasets needed for inference and evaluation.
Close Collaboration with Product Team: Translate research strategies into scalable, production-ready applications.
Production Integration: Collaborate with backend/frontend engineers to deploy and monitor AI features in real-world environments.
AI Pipelines: Build and maintain end-to-end pipelines that combine speech, and language components into reliable production workflows.
What You’ll Do
Own the full adaptation lifecycle: understand product needs and technical context, survey existing pre-trained models and techniques, prototype, evaluate, iterate, and deploy.
Work across ASR and acoustic modeling, NLP (generative and classical), applying the right pre-trained tool to each problem rather than building from scratch.
Partner with dynamic, cross-functional squads across engineering, research, product, and operations.
Apply practical, outcome-focused research methodologies, shaping solutions that directly serve product goals and customer needs.
Design evaluation frameworks and meaningful metrics that guide experimentation and drive continuous improvement.
Write production-ready Python code, integrating algorithms and models directly into Verbit’s platform.
Prioritize effectively using Pareto thinking, delivering high-value quick wins while supporting long-term strategic advancements.
Serve as a key technical member whose ideas, perspective, and ownership significantly influence the team’s direction.
What You Bring
Experience with data-driven applied AI work across one or more domains (speech, NLP, vision), including evaluation design and metric-driven experimentation.
3+ years of experience in applied AI or ML engineering, preferably 5+.
Hands-on expertise adapting pre-trained models — LLMs, ASR/acoustic models, models — in applied, product-oriented settings. Comfort matching existing techniques to problems rather than designing new algorithms.
Excellent Python engineering skills, with a strong track record translating prototypes into scalable ML or algorithmic solutions.
Strong understanding of model behavior, ML development workflows, experimentation processes, and fine-tuning / adaptation strategies.
Ability to work effectively in fast-paced, iterative environments and collaborate closely with engineering teams.
Fluency with AI coding agents and tools, and a habit of continuously adopting new ones — while still owning the engineering logic and the code you ship.
Who You Are
Positive, energetic, and proactive, with growth mindset and a strong sense of ownership.
A clear communicator who can make technical reasoning accessible across functions.
Motivated by creating real value for users and the business, and excited to contribute where impact is highest.
Flexible and comfortable adjusting priorities based on product needs and feedback.
A team-oriented contributor who thrives in dynamic, cross-disciplinary squads.
Eager to leverage AI coding assistants to move faster, but rigorous about reviewing, understanding, and taking responsibility for every line that goes in.
Nice to Have
Experience with real-time or streaming systems.
Background in speech processing, acoustic modeling, conversation intelligence, or multimodal AI pipelines.
Infrastructure knowledge (e.g., AWS), and familiarity with GitHub and Linux.
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