ML Operations Engineer

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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

• Serve as a force multiplier for development teams by creating golden paths that remove roadblocks and improve ideation and innovation • Collaborate with other engineers, product managers, and internal stakeholders in an Agile environment • Design and deliver tasks end-to-end with little guidance from Senior team members • Provide support to teams building and deploying AI applications by addressing common pain points in the MLDLC • Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities • Support the vision and values of the company through role modeling and encouraging desired behaviors. • Participate in various cross-functional company initiatives and projects as requested. • Evaluate frameworks, vendors, and tools that can be used to optimize processes and costs with minimal guidance.

🎯 Requirements

• Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred (or commensurate experience) • 3+ years of experience in hands-on development and deployment of Machine Learning algorithms and services • 3+ years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance • 3+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP) • Experience with at least 50% of:**PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, KubeFlow • Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement • Experience in cloud-native delivery, with practical understanding of containerization technologies such as Kubernetes and Docker • Proficiency in GitOps and creation/management of CI/CD pipelines • Demonstrated experience building and using SQL/NoSQL databases • Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools. • Good problem-solving skills with a focus on innovation, efficiency, and scalability in a global context. • Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions. • Ability to be a team player who can also work independently • Experience working across multiple development teams is a plus