Senior ML & AI Engineer

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SeniorZdalnieFull-time

#478866·Dodano wczoraj·0

Źródło: SPD Technology

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Tech Stack / Keywords

Python LangChain LangGraphLangSmithPyTorch Scikit-LearnspaCyTensorFlow SQL NLP

Podsumowanie oferty

Build and fine-tune generative AI and transformer models for the PitchBook Platform, which provides investment professionals with financial data and capital-markets insights. Develop scalable ML systems and NLP pipelines using Python, PyTorch, and frameworks including LangChain, LangGraph, and LangSmith.

Wymagania

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field.
5+ years of production experience in the ML field, including developing transformer-based models and deploying them in scalable systems.
Proficiency in Python and machine and deep learning frameworks such as TensorFlow, PyTorch, Scikit-Learn, and spaCy, or similar.
Experience with natural language processing and modern LLM-based techniques.
Experience with the full ML lifecycle, including data preprocessing, training, evaluation, and monitoring.
Skills in SQL and data extraction methods.
Excellent communication and collaboration skills.
English at upper-intermediate level or higher; Ukrainian fluent/native.

Nice to have:

Exposure to financial services, investment banking, venture capital, or private equity.

Obowiązki

Design, develop, and fine-tune generative AI models using transformer architectures.
Build automated pipelines and intelligent agents with LangChain, LangGraph, and LangSmith, integrating vector databases for similarity search and real-time analysis.
Process and analyze unstructured data using embeddings and statistical modeling to identify insights.
Collaborate with cross-functional teams to create production-grade ML systems for real-time, high-volume data processing.
Mentor junior team members and stay updated on Agentic AI, transformer models, and generative systems.
Work with Product and Engineering teams to improve data management and support innovation; present complex analyses clearly.
Use PyTorch, Scikit-Learn, and spaCy to build NLP pipelines, work with vector databases for high-dimensional embeddings, and develop hybrid models to extract insights from diverse data sources.

Benefity

Flexible working schedule.
Laptops and licensed software provided.
Performance and merit reviews, personal development plans, individual learning through the corporate library, and public-speaking support.
Company-wide tech and cultural events.
Referral bonus program.

Elastyczne godziny

Spotkania integracyjne

Premie

Inne informacje

Recruitment process: recruiter interview; technical interview (up to 90 minutes); system design interview (up to 45 minutes); behavioral round with the Product Manager (45 minutes); final interview with the Engineering Manager (30 minutes).

SPD Technology

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