ML Engineer (f/m/d)
ITRex Group · Serbia
- On site
- Full-time
- $130,000 / year
- Serbia
Job highlights
- Own end-to-end ML initiatives for a live-streaming platform.
- Develop and deploy scalable ML models.
- Collaborate with cross-functional teams.
- Optimize model performance and production systems.
- Impact user engagement and platform experience.
About the role
About ITRex Group
ITRex - AI pioneers who build systems that actually work in the real world, not just in demos. We're 250+ people spread across the US and Europe, creating solutions for companies like P&G and Shutterstock. We keep it simple, build it right, and focus on what works. We're the kind of people who don't ignore messages in Slack, who jump in to help when you're stuck on a problem, and who offer solutions instead of blame when things go sideways. We believe in openness, accountability, and having each other's backs. No office politics, no hidden agendas - just people who care about doing good work together and supporting each other to get there.The Role
We are looking for an ML Engineer to join a large-scale live-streaming and social interaction platform that powers multiple mobile applications for dating, communication, video chats, and live broadcasts. Every month, the platform delivers more than 1 billion minutes of live-streaming sessions to users worldwide. As an ML Engineer, you will take end-to-end ownership of ML initiatives: from problem discovery and requirements definition to solution design, implementation, deployment, and post-production optimization. You will work closely with Product, Engineering, Data, DevOps, and business stakeholders to design and deliver scalable ML-driven features that directly impact user engagement, matching quality, recommendations, moderation, and overall platform experience.Responsibilities
- Design, develop, and deploy machine learning models for predictive analytics, classification, NLP, and other data-driven tasks
- Implement data pipelines for ingestion, preprocessing, feature engineering, and model training
- Containerize ML models and applications using Docker for scalable and reproducible deployments
- Deploy and maintain ML solutions in cloud environments (AWS/Snowflake)
- Optimize model performance, latency, and resource utilization for real-time or batch inference
- Monitor and troubleshoot ML models in production, ensuring reliability and robustness
- Collaborate with Product, Engineering, Data, and business stakeholders to define project requirements and integrate ML models into production systems
- Conduct rigorous model evaluation using appropriate metrics to ensure performance and fairness
- Assess whether machine learning is necessary for a given problem or if alternative rule-based/statistical approaches are more appropriate
Requirements
Technical Skills
- 4+ years of experience as a Software Engineer, with at least 3 years in an ML Engineer role
- Strong understanding of machine learning techniques, including supervised & unsupervised learning, NLP, deep learning fundamentals, and model evaluation
- Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn, Pandas, and NumPy
- Hands-on experience in containerizing ML applications using Docker for scalable deployment
- Practical experience with at least one cloud provider (AWS, GCP)
- Strong background in working with large datasets, SQL/NoSQL databases
- Ability to decompose complex problems into well-structured ML tasks
- Skilled at assessing whether ML is the best approach or if a simpler solution (e.g., heuristic rules, statistical methods) would be more effective
- Expertise in debugging, optimizing, and enhancing models for performance, efficiency, and interpretability
- Experience maintaining ML workflows to ensure reproducibility, scalability, and operational efficiency
Business & Collaboration
- Excellent communication skills, capable of explaining ML concepts to both technical peers and non-technical stakeholders
- Collaborative, product-focused approach within Agile, cross-functional environments
- Proactive mindset with a strong sense of ownership with the ability to lead ML tasks end-to-end, from discovery and experimentation to production deployment and support
- Experience working closely with Product, Engineering, Data, DevOps, and business teams to align technical solutions with business goals
- Continuous learning mindset with awareness of current ML/AI trends, tools, and best practices
- English proficiency at an Upper-Intermediate level or above
Nice to have
- Understanding the business impact of ML models and how to align them with organizational goals
- Experience with feature stores, model registries, and ML model lifecycle management
- Experience designing and developing Retrieval-Augmented Generation (RAG) solutions
- Hands-on experience with AI tools in ML workflows
Benefits
Why people stay First, the foundation:- Remote flexibility: Work where and how you work best - we trust you to deliver
- Fair compensation: Competitive salary + benefits that matter (medical, wellness, learning)
- Ownership opportunities: See a problem worth solving? Own it. We back smart risks over bureaucratic safety
- AI enhancement: We leverage AI to make you faster and stronger - complementing your abilities, not replacing them
- Learning investment: English classes, professional development, well-being support
- Career progression: Real paths up, not just sideways shuffling
- Responsive teammates: No ignored Slacks, no "not my problem" attitudes
- Supportive culture: When you're stuck, people help. When things break, we fix them together
- Human connections: Regular meetups, tech talks, and actual relationships beyond work
Key skills/competency
- ML Engineer
- Machine Learning
- Python
- TensorFlow
- PyTorch
- Scikit-Learn
- Docker
- AWS
- NLP
- Data Pipelines
Skills & topics
- ML Engineer
- Machine Learning
- Python
- TensorFlow
- PyTorch
- Scikit-Learn
- Docker
- AWS
- NLP
- Data Pipelines
- Software Engineer
- Cloud Computing
- AI
- Deep Learning
- Predictive Analytics
- Remote
- Agile
How to get hired
- Tailor your resume: Highlight 4+ years of software engineering and 3+ years of ML engineering experience, emphasizing Python, ML frameworks (TensorFlow, PyTorch), Docker, and cloud platforms (AWS/GCP).
- Showcase problem-solving: Detail your experience in designing, deploying, and optimizing ML models for real-time inference and production environments.
- Demonstrate collaboration: Provide examples of working with Product, Engineering, Data, and business teams to align technical solutions with business goals.
- Highlight ownership: Emphasize your ability to lead ML tasks end-to-end and your proactive, product-focused approach within Agile settings.
- Prepare for technical and behavioral questions: Be ready to discuss ML techniques, model evaluation, debugging, and your collaborative approach.
Technical preparation
Master Python and core ML libraries.,Practice containerizing applications with Docker.,Build and deploy models on AWS/GCP.,Study ML lifecycle management principles.
Behavioral questions
Describe a complex ML problem you solved.,How do you explain ML to non-technical people?,Share an example of owning an ML initiative.,How do you collaborate with cross-functional teams?
Frequently asked questions
- What is the typical career progression for an ML Engineer at ITRex Group?
- At ITRex Group, ML Engineers can expect clear career progression paths focused on growth. This includes opportunities for increased ownership of ML initiatives, specialization in advanced AI/ML areas, and potential leadership roles. The company invests in professional development and offers chances to work on challenging, impactful projects that foster advancement.
- How does ITRex Group support continuous learning for its ML Engineers?
- ITRex Group actively supports continuous learning through various avenues. This includes investments in English classes, professional development programs, and access to resources for staying updated on the latest ML/AI trends, tools, and best practices. They also foster a culture of knowledge sharing through tech talks and by encouraging exploration of new AI tools.
- What kind of machine learning problems will an ML Engineer work on at ITRex Group?
- As an ML Engineer at ITRex Group, you will tackle a wide range of problems on a large-scale live-streaming platform. This includes developing models for predictive analytics, classification, Natural Language Processing (NLP), user engagement, matching quality, recommendation systems, and content moderation, all aimed at enhancing the user experience across multiple mobile applications.
- Is this an on-site, hybrid, or remote ML Engineer position at ITRex Group?
- ITRex Group offers remote flexibility for this ML Engineer position, allowing you to work where and how you work best. The company emphasizes trust in its employees to deliver results regardless of their physical location.
- What are the key technical skills required for the ML Engineer role at ITRex Group?
- Key technical skills for this ML Engineer role include 4+ years in Software Engineering with at least 3 years in ML, strong understanding of ML techniques (supervised, unsupervised, NLP, deep learning), proficiency in Python with frameworks like TensorFlow, PyTorch, and Scikit-Learn, experience with Docker, and familiarity with cloud providers like AWS or GCP. Experience with large datasets and databases is also crucial.
- How does ITRex Group ensure the reliability and robustness of its deployed ML models?
- ITRex Group ensures ML model reliability through rigorous monitoring and troubleshooting in production environments. They emphasize robust deployment practices using containerization (Docker), CI/CD pipelines, and continuous optimization of model performance, latency, and resource utilization. Their approach focuses on ensuring operational efficiency and maintaining model accuracy and fairness.