Software Engineer – Applied AI Research

Infotree Global Solutions

. Conceptualize, prototype, and rigorously evaluate state-of-the-art AI/ML models, engineering them into scalable, low-latency production applications .

Posted 11/3/2026full-timeWarsaw • PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI/ML models within financial contexts, emphasizing strong programming skills in Python, C++, and Java. Proven ability to design scalable infrastructure and maintain high code quality standards while collaborating with quantitative teams.

Highest-signal resume keywords

AI/ML Model DevelopmentSoftware Engineering LeadershipQuantitative Investment WorkflowsPython ProgrammingCloud Architecture

ATS Keywords

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Hard Skills

Machine LearningDeep LearningSoftware DevelopmentData StructuresAlgorithmsConcurrencyQuantitative AnalysisStatistical ModelingProduction-Grade ApplicationsAutomated Testing

Soft Skills

Technical LeadershipCollaborationAdvocacy for Code Quality

Tools & Technologies

Cloud ComputingDistributed ComputingHPCTesting FrameworksModular Libraries

Certifications & Qualifications

Master’s or PhD in Computer ScienceMachine Learning Certification

Industry Keywords

EquitiesFixed IncomeMulti-AssetQuantitative FinanceFinancial Time-Series Data

Tech Stack

Tools & technologies

CloudJavaPythonC++

About the role

Key responsibilities & impact

Conceptualize, prototype, and rigorously evaluate state-of-the-art AI/ML models, engineering them into scalable, low-latency production applications
Design and implement modular libraries, testing frameworks, and scalable infrastructure for the quantitative research and deployment lifecycle
Embed AI solutions into workflows across Equities, Fixed Income, and Multi-Asset strategies
Provide hands-on technical leadership, set code quality standards, and advocate for software engineering and system reliability
Partner with quantitative researchers, portfolio managers, and global engineering teams
Represent the organization at industry conferences and contribute to open-source initiatives where appropriate
Potentially take novel ML/AI models from experimentation into high-availability production environments
Work with financial time-series data, massive structured datasets, portfolio analytics, distributed computing, cloud architectures, or HPC

Requirements

What you’ll need

Master’s or PhD in Computer Science, Machine Learning, Mathematics, Statistics, Physics, Quantitative Finance, or a related quantitative discipline, or equivalent demonstrably deep industry experience
5+ years of software engineering experience building robust, production-grade applications within finance, quantitative technology, or related data-intensive domains
Exceptional programming skills in Python, C++, Java, or modern object-oriented/functional languages
Solid computer science fundamentals, including data structures, algorithms, and concurrency
Practical experience designing, training, evaluating, and deploying modern machine learning or deep learning systems
Hands-on experience developing software supporting quantitative investment workflows
Solid grasp of asset classes, including Equities, Fixed Income, or Multi-Asset
Deep commitment to clean architecture, automated testing, continuous integration, scalability, and maintainability

Benefits

Comp & perks

Supportive team environment
Opportunities to grow and challenge yourself in the role
Consultant care representatives committed to employee success and well-being