应用AI与机器学习工程经理
Engineering Manager, Applied AI & Machine Learning Engineering
在SPD Technology,我们汇聚了一群志同道合的人,他们通过工作创造价值,致力于高绩效,并提供定制化的前沿技术解决方案,推动客户的增长。我们以卓越的文化赋能员工,为他们提供承担责任、在每个层面做出贡献的机会。我们重视人性与协作,鼓励专业和个人成长,营造一个支持性强、灵活的工作环境,欢迎每个人贡献自己的力量。
现在,我们正在寻找一名工程经理,负责应用人工智能和机器学习工程,加入我们的团队。
职位简介
PitchBook 是一个面向投资专业人士的平台。我们的软件提供数据访问和分析工具,快速获取答案并发现有前景的机会。从超过三百万家公司的财务数据中挖掘出可操作的见解和趋势。全球用户包括大型企业、初创公司、风险投资和私募股权公司、投行等。
作为人工智能/机器学习工程经理,您将支持一个由 MLE 和 MLOps 工程师组成的跨职能团队,他们在多个 AI/ML 项目中工作。
您的主要职责将包括资源规划、执行和人员管理。您将与项目负责人、技术负责人、职能经理和产品合作伙伴紧密合作,确保项目人员配置合理,计划切实可行,风险可见,团队能够高效交付。
您将管理多个项目的容量和资源分配,协助协调依赖关系和优先级,并向利益相关者清晰展示交付进展。项目和技术负责人将继续负责产品方向和技术决策。
您还将支持团队成员的职业发展和绩效。这包括收集反馈、辅导员工、制定发展计划,并参与绩效、晋升和薪酬评估。
您应具备足够的 AI/ML 经验,能够理解工作内容,与工程师有效沟通,并识别技术交付风险。但此职位不期望您从事实际的工程或架构工作。
我们的技术栈与关注领域
- 生成式 AI 与大语言模型(LLM):开发和维护基于 LLM 的生成功能解决方案。
- 经典机器学习模型:开发和维护预测和分类模型。
查看英文原文
At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed.
And now we are looking for a Engineering Manager, Applied AI & Machine Learning Engineering to join us as part of our team.
About Role
PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others.
As an Engineering Manager, AI/ML, you will support a cross-functional team of MLE and MLOps engineers working across several AI/ML initiatives.
Your primary focus will be resource planning, execution, and people management. You will work closely with project leads, technical leads, functional managers, and product partners to ensure projects are appropriately staffed, plans are realistic, risks are visible, and teams can deliver effectively.
You will manage capacity and resource allocation across multiple projects, help coordinate dependencies and priorities, and provide stakeholders with a clear view of delivery progress. Project and technical leads will continue to own product direction and technical decisions.
You will also support the career growth and performance of team members. This includes gathering feedback, coaching employees, creating development plans, and contributing to performance, promotion, and compensation reviews.
You should have enough AI/ML experience to understand the work, communicate effectively with engineers, and identify technical delivery risks. However, this is not expected to be a hands-on engineering or architecture role.
Our Tech Stack & Focus Areas
- Generative AI & LLMs: Develop and maintain LLM-based solutions for generative features.
- Classic ML Models: Develop and maintain predictive and classification models for financial data
- Vector Databases: Implementing efficient storage and retrieval systems for high-dimensional data embeddings.
- Embeddings: Developing hybrid models to extract insights from diverse data sources.
- High-Volume Data Management: Engineering systems capable of handling massive, real-time data streams.
Work Environment
Flexible schedule with participation in team ceremonies and cross-functional collaboration. Time zone: Europe/Kyiv.
As a qualified expert, You will:
- 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 a clear view of project progress, dependencies, risks, and resource constraints
- Help resolve delivery blockers, priority conflicts, and cross-team dependencies
- Facilitate quarterly and ongoing planning across MLEs and MLOps teams
- Provide clear delivery and staffing updates to functional managers and other 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
We’re looking for you if you have
- 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 points
- Experience managing or supporting MLE and MLOps teams
- Experience working in a matrix organization with separate people, project, product, and technical leadership roles
- Experience with planning or allocating engineers across multiple projects
- Familiarity with production ML, generative AI, semantic search, summarization, prediction, or similar capabilities
- Familiarity with technologies such as Kubernetes, Docker, Kafka, Airflow, Snowflake, and cloud platforms
- Experience conducting performance reviews and building employee development plans
- Experience working with staffing partners, contractors, or blended internal and external teams
- Experience in fintech, SaaS, market data, or another data-intensive industry
Reveal great tech solutions
Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients.
Experience an agile and flexible working environment
Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work.
Embrace the opportunity for personal and professional growth
Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learnings through the corporate library, public speaking support, and more.
Be among like-minded people
Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program.
Interview Steps:
- Pre-screening with recruiter
- EM & HRBP Interview
- Technical Interview
- Final сlient Interview
Originally posted on Himalayas