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

Information Technology

Founded 2006

17 open positions

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Senior ML Operations

1 month, 2 weeks 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

Internet Software & Services

Founded 2006

View All Jobs 17

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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