Engineering Manager – Applied AI, Machine Learning

🔥 0 minutes ago

🌐 Ukraine, Poland, +4 more countries – Remote

🇺🇦 Ukraine – Remote 🇵🇱 Poland – Remote 🇪🇸 Spain – Remote 🇵🇹 Portugal – Remote 🇩🇪 Germany – Remote 🇷🇴 Romania – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♀️ Software Engineering Manager

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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SPD Technology

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2006

💳 Fintech

🤖 Artificial Intelligence

🤝 B2B

Fintech • Artificial Intelligence • B2B

SPD Technology is a global software product development company that delivers custom digital platforms, cloud and DevOps, AI/ML, and fintech/payment solutions. They specialize in application modernization, data analytics and engineering, system integration and APIs, security and quality engineering, and mobile/web UX/UI development. SPD works as a B2B partner for enterprise and growth-stage clients (notable customers cited include PitchBook and Poynt), focusing on building payment systems, billing and fraud-detection software, data platforms, and AI-enabled products for industries such as fintech, insurance, healthcare, and e-commerce.

📋 Description

• Support a cross-functional team of MLE and MLOps engineers working across several AI/ML initiatives • Manage resource allocation and capacity planning across multiple AI/ML projects and operational commitments • Partner with project and technical leads to create realistic delivery plans, milestones, and staffing models • Maintain visibility into project progress, dependencies, risks, and resource constraints • Help resolve delivery blockers, priority conflicts, and cross-team dependencies • Facilitate quarterly and ongoing planning across MLE and MLOps teams • Provide delivery and staffing updates to functional managers and stakeholders • Manage and coach engineers through regular one-to-one meetings and career discussions • Gather and synthesize feedback from project leads, technical leads, and cross-functional partners • Create development plans and support performance, promotion, and compensation review processes • Identify team capability gaps and contribute to hiring, onboarding, retention, and workforce planning • Foster an inclusive, collaborative, and high-performing team environment • Apply Agile, Lean, and Fast-Flow practices to improve team effectiveness and delivery predictability • Understand AI/ML work, communicate effectively with engineers, and identify technical delivery risks; this is not a hands-on engineering or architecture role

🎯 Requirements

• At least three years of experience in software engineering, AI/ML, or a related field • At least three years of experience in people management, engineering management, or technical program leadership • Working knowledge of AI/ML modeling, systems and the development lifecycle • Experience managing multiple technical projects with shared resources and cross-team dependencies • Strong skills in capacity planning, resource allocation, project execution, risk management, and stakeholder communication • Experience supporting the performance and career development of technical employees • Ability to understand technical discussions and work effectively with MLE and MLOps teams • Experience working with distributed or geographically dispersed teams • English — Upper Intermediate or higher • Ukrainian — fluent • Bonus: Experience managing or supporting MLE and MLOps teams • Bonus: Experience working in a matrix organization with separate people, project, product, and technical leadership roles • Bonus: Experience with planning or allocating engineers across multiple projects • Bonus: Familiarity with production ML, generative AI, semantic search, summarization, prediction, or similar capabilities • Bonus: Familiarity with Kubernetes, Docker, Kafka, Airflow, Snowflake, and cloud platforms • Bonus: Experience conducting performance reviews and building employee development plans • Bonus: Experience working with staffing partners, contractors, or blended internal and external teams • Bonus: Experience in fintech, SaaS, market data, or another data-intensive industry

🏖️ Benefits

• Fully remote work • Flexible working schedule • Stable workload and stable income • Provided laptops and licensed software • Performance and merit reviews • Personal development plans • Individual learnings through the corporate library • Public speaking support • Company-wide tech and cultural events • CSR initiatives • HR support • Referral bonus program