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Senior ML Operations

3 weeks, 2 days ago
Spain, Poland, Portugal, Romania, Ukraine
Full-time
Senior
Machine Learning Engineer
DevOps and Infrastructure
Agile AWS Azure CI/CD Docker Elasticsearch FastAPI GCP GitOps Grafana Java Kafka Kubeflow Kubernetes MLflow Prometheus Python PyTorch Redis Scikit-learn Scrum SQL TensorFlow
Apply Now
SPD Technology

SPD Technology

SPD Technology specializes in custom software product development, focusing on fintech and payment solutions, as well as AI/ML solutions, data engineering, and cloud services to help businesses leverage technology for growth and innovation.

Internet Software & Services
Founded 2006
View All Jobs 10

Description

  • Serve as a force multiplier for development teams by creating golden paths that remove roadblocks and improve ideation and innovation.
  • Collaborate with engineers, product managers, and internal stakeholders in an Agile environment.
  • Provide mentorship, technical guidance, and code reviews for team members.
  • Design and deliver projects end-to-end with little to no guidance.
  • Support teams building and deploying AI applications by addressing common pain points in the machine learning development, deployment, and support lifecycle.
  • Evaluate frameworks, vendors, and tools to optimize processes and costs with minimal guidance.
  • Contribute to strategic planning to ensure the team builds products that deliver real business value.
  • Participate in cross-functional company initiatives and projects as requested.
  • Learn and apply new tools, technologies, libraries, and frameworks to improve PitchBook’s AI capabilities.
  • Support company vision and values through role modeling and encouraging desired behaviors.

Requirements

  • Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred, or equivalent practical experience.
  • 5+ years of hands-on software development experience with Python; Java experience with strong Python proficiency is also considered.
  • 4+ years of experience designing and building distributed software systems and architectures.
  • 3+ years of hands-on experience deploying and operating machine learning services in production.
  • Experience supporting ML lifecycle operations, including post-deployment monitoring and maintenance.
  • Experience with a cloud-native stack and containerization technologies such as Kubernetes and Docker.
  • Demonstrated experience with SQL and NoSQL database design and implementation.
  • Ability to decompose complex problems into iterative, well-defined solutions.
  • Strong problem-solving skills focused on building scalable, efficient, and maintainable systems.
  • Strong communication and collaboration skills with the ability to work effectively across cultures and regions.
  • Ability to work independently and as part of a team.
  • Experience working across multiple development teams is a plus.
  • Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure is preferred.
  • Proficiency in GitOps practices and CI/CD pipeline development and management is preferred.
  • Experience with observability and monitoring tools such as Prometheus and Grafana is preferred.
  • Experience provisioning and managing large language models through managed services such as Azure OpenAI, Google Vertex AI, or Amazon Bedrock is preferred.
  • Hands-on experience with LLM gateways such as LiteLLM and agentic frameworks such as LangGraph or LangSmith is preferred.
  • Practical experience with vector embedding models and vector databases such as Pinecone, Weaviate, Milvus, or pgvector is preferred.
  • Experience building retrieval-augmented generation systems and evaluating retrieval and generation performance is preferred.
  • Cloud-native experience with services like Amazon SageMaker, Google Vertex AI, or Azure ML is preferred.
  • Familiarity with ML frameworks and tools such as PyTorch, TensorFlow, and scikit-learn is preferred.
  • Experience with data infrastructure such as Redis, Elasticsearch, and Apache Kafka is preferred.
  • Experience with ML experiment tracking and model management tools such as Weights & Biases, MLflow, or KubeFlow is preferred.
  • API development experience with FastAPI or similar frameworks is preferred.
  • Java programming experience is a plus.

Benefits

  • Fully remote work with a flexible working schedule.
  • Stable workload and stable income.
  • Provided laptop and licensed software.
  • Performance and merit reviews.
  • Personal development plans and individual learning opportunities.
  • Access to a corporate library and public speaking support.
  • Company-wide tech and cultural events.
  • Referral bonus program.

Interested in this position?

Apply directly on the company website

Apply Now

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