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Machine Learning Engineer (Remote)

Roles & Responsibilities

  • Strong understanding of business context and how ML can create value
  • Proficiency in Python and PyTorch with experience in ML tooling and data platforms (SQL, ClickHouse), and cloud services (AWS including SageMaker, EC2, EKS, EMR)
  • Experience establishing and maintaining MLOps practices (versioning models, automated testing, CI/CD) and containerization (Docker); proficient with FastAPI, Kafka, and Airflow
  • Experience with LLMs and GenAI applications is a plus; intermediate English; fintech/mobile app/gaming experience is a plus

Requirements:

  • Collaborate with Sales, Marketing, Products, Payments, and Dealing to translate business needs into scalable ML solutions
  • Work on projects such as LTV prediction, churn prediction, antifraud/fraud prevention, uplift modeling, and GenAI applications
  • Oversee current ML solutions, drive improvements, and expand ML adoption across the organization
  • Establish and advance MLOps practices for model development, deployment, monitoring, and CI/CD; support LLM projects (chatbots, knowledge bases)

Job description

Libertex Group Overview 

Established in 1997, the Libertex Group has helped shape the online trading industry by merging innovative technology, market movements and digital trends. 

The multi-awarded online trading platform, Libertex, enables traders to access the market and invest in stocks or trade CFDs with underlying assets being commodities, Forex, ETFs, cryptocurrencies, and others.

A firm believer in the power of sports to inspire, empower and push for success, Libertex is the Official Online Trading Partner of KICK Sauber F1 Team.

We build innovative fintech so people can #TradeForMore with Libertex.


Job Overview 

We are looking for a Senior Machine Learning Engineer who will play a pivotal role in implementing, enhancing, and maintaining our machine learning solutions.

Responsibilities:

  • Work closely with business departments (Sales, Marketing, Products, Payments, Dealing) to understand their needs and translate these into practical, scalable, and robust machine learning solutions.
  • Work on such projects like LTV prediction, churn prediction, antifraud solutions, uplift modelling, GenAI-applications
  • Oversee current solutions, manage improvements if needed, expand the role of machine learning across organisation.
  • Implement new and improve current MLOps practices, laying the foundation for efficient and effective model development, deployment, and monitoring.
  • Implement new and support existing LLM projects (chatbots, knowledge base etc).

Requirements

  • Great understanding of business and where ML solutions can fit and bring value
  • Technological stack - Python, PyTorch,, SQL (MSSQL, Postgres), ClickHouse, AWS (Sagemaker, EC2, EKS, EMR), Docker, FastApi, Kafka, Airflow
  • Establishing and maintaining MLOps practices, including version control for models, automated testing, and CI/CD for ML systems
  • Utilise AWS ML (or similar) services for developing and deploying models
  • General understanding of IT infrastructure, various data source types, development processes etc.
  • Great to have previous experience in applying data science tools to mobile apps, gaming or fintech
  • Intermediate level of English
  • Experience with LLMs is a huge plus (AWS Bedrock, langchain, langgraph, RAG, Agents, MCP)

Benefits

  • Quarterly bonuses based on Company performance
  • Generous relocation package for the employee and their immediate family/partner 
  • Medical Insurance Plan with coverage for the employee and their immediate family from day one
  • 24 working days of annual leave 
  • Yearly reimbursement of travel expenses for the employee and family's flight home
  • Corporate events and team building activities
  • Udemy Business unlimited membership & language training courses 
  • Professional and personal development opportunities in a fast-growing environment 

Libertex Group is an equal opportunity employer, fostering an inclusive and diverse environment. We do not discriminate based on any characteristic protected by the law. Candidate privacy is respected, and all data is securely stored and used solely for recruitment purposes, in line with GDPR and our internal policies. Unsuccessful applicants may have their data retained for future opportunities unless deletion is requested.

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