Вакансия Senior Machine Learning Engineer

Skills

• Python
• Pandas
• NumPy
• LLM
• RAG
• FAISS
• NLP
• Hugging Face Transformers
• Hydra
• Git
• Github

Описание вакансии

Svitla Systems Inc. is looking for a Senior Machine Learning Engineer with NLP and/or LLM for a full-time position (40 hours per week) in Ukraine.Our client is an American mobile computing company that manufactures and sells marking, tracking, and computer printing technologies, its products include mobile computers and tablets, software, thermal barcode label and receipt printers, RFID smart label printers/encoders/fixed & handheld readers/antennas, autonomous mobile robots (AMRs) & machine vision (MV), fixed industrial scanning hardware & software.These technologies serve a wide range of industries, including retail, healthcare, manufacturing, logistics, transportation, hospitality, energy, and utilities. The company focuses on enabling real-time visibility and workflow automation for frontline workers, providing solutions that enhance productivity, safety, and business intelligence across entire supply chains and operations. The award-winning portfolio spans software to innovations in robotics, machine vision, automation, and digital decisioning, all backed by a +50-year legacy in scanning, track-and-trace, and mobile computing solutions. With an ecosystem of 10,000 partners across more than 100 countries, the customers include over 80% of the Fortune 500.The central innovation team is composed of engineers and researchers in London, Europe, the US, India, and Shanghai, about 90 people. They provide AI innovation and acceleration for the business units and are working on CV and GenAI solutions with an emphasis on device inference (mostly Qualcomm chipsets). Researchers create/fine-tune models and pass them over to the engineering team to optimise, quantise, etc. Then the team builds an application solution with the customers to show value.

Requirements

• Expertise in programming, problem-solving, and machine learning (ML) and artificial intelligence (AI).
• Strong programming knowledge, particularly in Python, and experience using key data manipulation libraries such as Pandas and NumPy.
• A solid background in machine learning, particularly in classification and retrieval tasks.
• Hands-on experience with large language models (LLMs), including fine-tuning for specific use cases, retrieval-augmented generation (RAG), foundation models APIs, and prompt engineering.
• Familiarity with Faiss for efficient nearest-neighbor search in retrieval tasks.
• A strong understanding of Natural Language Processing (NLP) is preferred, with experience in audio/voice manipulation tasks, specifically text-to-speech (TTS) and speech-to-text (STT).
• Familiarity with the Hugging Face Transformers and Datasets libraries.
• Solid knowledge of tools such as Hydra for configuration management and Weights & Biases for tracking experiments.
• Experience with Git and GitHub for version control and a proven ability to collaborate effectively in a team environment, particularly when working on shared codebases and remote projects.
• Strong understanding of data management and manipulation, experience working on remote servers to develop and deploy machine learning models.
• While candidates with expertise in both NLP and LLM are preferred, we are open to individuals with strong experience in either area who can contribute effectively to the projects.

Responsibilities

• Design, develop, and deploy machine learning solutions with a focus on Natural Language Processing (NLP) and Large Language Models (LLMs).
• Fine-tune large language models for domain-specific applications, including retrieval-augmented generation (RAG), prompt engineering, and leveraging foundation model APIs.
• Build and optimize classification, retrieval, and recommendation systems.
• Conduct experiments, track results, and optimize model performance using tools such as Hydra and Weights & Biases.
• Work with audio/voice processing technologies, including text-to-speech (TTS) and speech-to-text (STT).
• Implement efficient similarity and nearest-neighbor search using Faiss and other retrieval frameworks.
• Collaborate with cross-functional teams to integrate ML models into production systems and deliver scalable, real-world solutions.
• Manage and manipulate large datasets, ensuring high data quality and reproducibility.
• Contribute to shared codebases with strong use of Git/GitHub, following best practices for version control and code reviews.
• Prepare clear documentation, procedural guidelines, and technical reports for both internal and external stakeholders.
• Provide mentorship and technical guidance to junior engineers where needed.
• Support the deployment and monitoring of ML systems on remote servers, ensuring stability and continuous optimization.