Machine Learning Engineering Lead

About Us

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 Machine Learning Engineering Lead to join us as part of our team.

About The 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.

We're looking for a highly hands-on Machine Learning Engineering Lead to drive the delivery of production-grade ML services. Your mission is to act as the primary technical driver for a team that bridges the gap between data science and enterprise software engineering, focusing on Machine Learning as a Service (MLaaS). As a coding leader, you will work with your team to deliver:

• Model as a Service: Design, code, and productionalize models into robust, model-driven services for use in product features.
• Service Enhancement: Directly implement advanced ML integrations to improve existing products.
• End-to-End MLDLC: Actively build and manage the pipelines that take models from experimentation to full production-grade deployment
  
  

The ideal lead is an experienced software engineer at their core, balancing high-level system design with specialized ML awareness. You are expected to be a hands-on contributor while leading the technical standard for the team.

• Hands-on Engineering Excellence: Lead the design, breakdown, and implementation of scalable, secure, and maintainable software solutions. Write clean, efficient, and well-documented code.
• Full Cycle Delivery: Take ownership of the transition from data science experimentation to productionized services, coding the integration layers, communication interfaces, and cloud deployment..
• Best Practices via Leading by Example: Lead the engineering SDLC practices through rigorous code reviews, pair programming, and automated testing.
• Infrastructure Mastery: Utilize, build, and adjust MLOps infrastructure (CI/CD, Kubernetes, Docker, clouds) to optimize the team's delivery pace.
  
  

Team setup: 1 Engineering Manager, 6 ML & AI Engineers.

Technical Stack: Python, Classic ML, LLM toolkits, Langchain, Langsmith, AWS, GCP, AWS Sagemaker, Kafka, Prometheus, Grafana, Fast API.

Work Environment: The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology.

As a qualified expert You will

• Technical Execution & Implementation (Primary Focus)
• Scalable Systems: Lead design and build high-performance, production-grade systems that handle real-time, high-volume data processing.
• Integration Ownership: Serve as the lead developer collaborating with cross-functional product delivery teams to seamlessly integrate ML models into the broader enterprise infrastructure.

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• Complex Troubleshooting: Dive deep into the codebase to foresee or troubleshoot and resolve the most complex technical, architectural, and deployment issues.
• Innovation: Experiment with and implement emerging trends in ML, Agentic AI, LLMs, and GenAI to identify practical opportunities for product improvement.
• Technical Leadership & Enablement
• Technical Mentorship: Act as the primary technical mentor for MLEs, fostering engineering culture by leading by example and spreading knowledge.
• Delivery & Governance: Help to translate business needs into technical solutions and drive sprint execution to ensure high-quality, timely feature releases

We're looking for you if you have

• Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred (or commensurate experience)
• Experience: 8+ years in software engineering with experience acting as a technical lead while maintaining active, hands-on coding responsibilities.
• 3+ years of experience in hands-on development and deployment with Python. Strong coding proficiency in Python for service development, model building, data extraction, and ML model management.
• 3+ years of experience in engineering microservice architectures, including post-deployment operations such as monitoring and maintenance
• 3+ years of experience and expertise in Amazon Web Services (AWS) and/or Google Cloud Platform (GCP), Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, FastAPI, Prometheus, Grafana, and Apache Kafka
• Experience with AI/ML development and delivery. Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow. Hands-on experience with LLM toolkits like LangChain, LangGraph, or LangSmith
• Ability to break large, complex solutions into well-defined stories/tasks, ensuring iterative development and continuous improvement by the ML Engineering team. Systems thinking and system design experience
• Experience in cloud-native delivery, with practical understanding of containerization technologies
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Good problem-solving skills with a focus on innovation, efficiency, and scalability in a global context
• Communication: Ability to propose and discuss complex technical architectures and analyses clearly to both engineering teams and stakeholders.
• Experience working with cross-team dependencies with multiple development teams is a plus
• Fluent Ukrainian, both spoken and written, for effective day-to-day communication with the team
  
  

Bonus points

• Observability and monitoring: Integration experience with observability tools (Prometheus, Grafana) and building instrumented, production-ready systems
• LLM Infrastructure: Experience provisioning and managing large language models through managed services (Azure OpenAI, Google Vertex AI, Amazon Bedrock)
• LLM Tooling: Hands-on experience with LLM gateways (LiteLLM) and agentic frameworks (LangGraph, LangSmith, or similar)
• Vector Systems: Practical experience with vector embedding models and vector databases (Pinecone, Weaviate, Milvus, pgvector)
• RAG Systems: Experience in retrieval-augmented generation systems engineering and evaluating
• ML experiment tracking and model management: Weights & Biases, MLflow, KubeFlow
• API development with FastAPI or similar frameworks. Java programming experience is a plus
  
  

What's in it for You

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

• Interview with the TA Specialist
• Technical Interview
• Interview with Engineering Manager
• Client Interview
• Executive Interview
  
  

Requirements

Benefits