Machine Learning Engineer

BigD are seeking a proactive and motivated Machine Learning Engineer to join our vibrant team. As an ML Engineer, you will play a crucial role in designing, developing, and deploying scalable machine learning models, optimizing model performance, and bridging the gap between data science research and production environments. We are interested in a full-time position.

We invite those who are fired up to

— Design, train, and deploy ML models into production environments

— Optimize model performance, scalability, and latency for high-load services

— Develop and maintain ML pipelines (data ingestion, feature engineering, training, and evaluation)

— Implement MLOps practices to streamline model deployment, monitoring, and retraining

— Collaborate with Data Engineers to ensure high-quality data pipelines and feature stores

— Explore new ML techniques and frameworks to solve complex business problems

— Maintain comprehensive documentation for models, experiments, and production infrastructure

Essential professional experience

— 2+ years of professional experience in an ML Engineer or Data Scientist role with a focus on production systems

— Proficiency in Python and deep understanding of core ML libraries (e.g., Scikit-learn, Pandas, NumPy)

— Hands-on experience with deep learning frameworks (e.g., PyTorch or TensorFlow)

— Experience with production deployment of ML models (FastAPI, Flask, or similar)

— Strong experience with MLOps tools and workflow orchestration (e.g., MLflow, Airflow, Kubeflow)

— Solid knowledge of SQL and experience working with relational databases and data warehouses (PostgreSQL, AWS, etc.)

— Proficiency in containerization and cloud orchestration (Docker, Kubernetes, AWS/GCP/Azure)

— Strong foundation in statistics, probability, linear algebra, and machine learning theory

We also appreciate

— Self-motivated with a strong ownership mentality and ability to deliver results independently

— Excellent problem-solving skills and attention to detail

— Ability to translate business requirements into technical ML solutions

— Strong communication skills for cross-functional collaboration with product and engineering teams

Working conditions:

• Direct communication with the core TEAM
• 28 calendar days of vacation
• Paid sick leave
• Sports compensation
• Compensation for courses and training
• Day off for birthday
• Flexible work schedule
• Regular salary reviews
• Salary paid at a favorable rate
• Non-toxic work environment, free of bureaucracy

• Stable salary payment

   

Join a fast-growing team at the forefront of the iGaming industry, where your expertise will directly contribute to the company's growth and success.