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Middle ML Operations

2 hours, 15 minutes ago
Spain, Poland, Portugal, Romania, Ukraine
Full-time
Mid Level
Machine Learning Engineer
DevOps and Infrastructure
Agile Apache Airflow AWS Azure CI/CD Docker Elasticsearch FastAPI GCP GitOps Grafana Java Kafka Kubeflow Kubernetes LLM Machine Learning MLflow MongoDB Prometheus Python PyTorch Redis Scikit-learn 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 13

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/Scrum environment.
  • Design and deliver tasks end-to-end with minimal guidance from senior team members.
  • Support teams building and deploying AI applications by addressing common pain points across the MLDLC.
  • Evaluate frameworks, vendors, and tools to optimize processes and costs.
  • Continuously learn and apply new tools, technologies, libraries, and frameworks to improve PitchBook’s AI capabilities.
  • Support the company’s vision and values through role modeling and encouraging desired behaviors.
  • Participate in cross-functional company initiatives and projects as requested.
  • Build and improve cloud-native ML systems, including deployment, monitoring, and maintenance.
  • Contribute to LLM, RAG, and other advanced AI infrastructure efforts where applicable.

Requirements

  • Degree in Computer Science, Information Systems, Machine Learning, or a related field preferred, or commensurate experience.
  • 3+ years of hands-on development and deployment of machine learning algorithms and services.
  • 3+ years of experience supporting the full MLDLC, including post-deployment monitoring and maintenance.
  • 3+ years of experience with AWS and/or Google Cloud Platform.
  • Experience with at least 50% of the following: PyTorch, TensorFlow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, or KubeFlow.
  • Experience with cloud-native delivery and containerization technologies such as Kubernetes and Docker.
  • Proficiency in GitOps and creating/managing CI/CD pipelines.
  • Demonstrated experience building and using SQL and NoSQL databases.
  • Strong Python skills; Java experience is a plus.
  • Ability to break complex problems into clear, iterative steps and improve solutions continuously.
  • Strong problem-solving, communication, and collaboration skills across global teams and cultures.
  • Experience working across multiple development teams is a plus.
  • Preferred experience with Azure, LLM infrastructure, vector databases, RAG systems, and agentic frameworks.
  • Preferred experience with observability tools such as Prometheus and Grafana in production systems.

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 and support from HR.

Interested in this position?

Apply directly on the company website

Apply Now

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