RA Machine Learning Interface Engineer

SmartRecruiting is looking on behalf of its client for a hardworking and creative Machine Learning Interface Engineer.

Location: Bucharest

Company mission:

DataTech company operating in the financial and professional services sector. We are creating a privacy preserving, sector agnostic, plug and play, data access and data collaboration platform at a scale that makes it critical infrastructure.


  • As a developer in Machine Learning (ML) interfaces, you will apply your expertise of designing and building distributed systems to develop ML pipelines all through training and deployment into production. 
  • Understanding the requirements of the ML research team, articulating them to the rest of the technical team.
  • Building and deploying a Federated Learning framework built on principles of modularity, scalability & maintainability.
  • Owning, designing, developing, and testing all necessary API’s predominantly in Python (with the option to leverage other languages including Java and Go) to RegulAition’s standards, quality and architecture.


  • Advanced Computer Science knowledge, e.g. development and code review best practices, software engineering, algorithms, data structures, object-oriented design, design patterns and microservices.
  • Advanced knowledge in parallel and distributed computing – messaging, microservices-based architectures, Big Data architectures such as Hadoop/Spark, containerisation, orchestration etc.
  • Proficiency in Java or another non-scripted language.
  • Demonstrable knowledge of Python and ability to drive the ML ecosystem/architecture.
  • Familiarity with Machine Learning concepts and interacting with models produced using industry-standard Python libraries.
  • Proficiency in service construction and development of RESTful APIs in Python, knowledge of Swagger or Postman.
  • Working knowledge of integrating with cloud hosting providers such as AWS or GCP.
  • Knowledge of DevOps tools such as Kubernetes (and Ingress), message brokers (e.g. RabbitMQ) and CI/CD, including GitLab CI or Jenkins.
  • Knowledge of NoSQL databases (e.g. MongoDB or PostgreSQL).
  • Good communication skills in order to collaborate on productionising
  • ML/NLP projects with the other data scientists and/or interact with RegulAItion’s clients in order to pitch/present on your ML implementation, including articulating in  UML.

Nice to have:

  • Master’s Level qualification in a CS/Engineering or a numerically intensive field.
  • Good theoretical grounding and practical experience in core machine learning concepts, techniques and frameworks, Deep Learning frameworks (e.g. Tensorflow, PyTorch or Keras) and traditional Python ML libraries (e.g. Scikit-learn, Pandas, NumPy, Keras, Gensim, NLTK or spaCy)
  • AWS certification
  • Knowledge of Federated Learning
  • Knowledge of ELK / ELG
  • Knowledge of distributed ledger technologies e.g. Hyperledger Fabric
  • Understanding of authentication and authorization protocols, e.g. OAuth 2.0
  • Knowledge of Ray Core and Ray Tune

Other info:

  • You will operate on a “remote work first” basis, offering competitive packages.

Contact Person:

Robert BEU

Managing Director

E: robert@smartrecruiting.ro


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