Senior ML Engineer

Are you GAME to JOIN US and be our new Senior ML Engineer?

SoftConstruct is on a search for a new player to join our AI Center of Excellence Department

We are seeking an experienced Senior Machine Learning Engineer who can apply strong AI expertise to prototype, develop, and deploy machine learning models. The Senior ML Engineer will collaborate with cross-functional teams to build AI products end-to-end: from ideation and design to deployment and integration into production systems. The role requires a broad skill set in machine learning engineering and a proven ability to lead projects independently.

Responsibilities

• Design, develop, and deploy machine learning models and pipelines to solve complex business problems
• Apply expertise in machine learning, optimization, and software engineering to create scalable AI solutions
• Collaborate with technical and business stakeholders to ensure seamless integration of ML models into production systems
• Guide and mentor junior engineers, advocate for engineering best practices, and contribute to the recruitment of technical talent
• Build and optimize data pipelines, ETL processes, and model-serving frameworks
• Drive innovation through effective problem-solving and identification of opportunities to leverage machine learning
• Monitor, debug, and enhance model performance and reliability in production environments

Requirements

• Bachelor’s degree in computer science, engineering, statistics, mathematics, or a related field (advanced degree preferred)
• 5+ years of hands-on experience building and deploying machine learning models in production
• Strong software engineering skills, including experience with Python, version control systems (e.g., Git), and ML frameworks (e.g., TensorFlow, PyTorch, or Scikit-learn)
• Proficiency in building and optimizing scalable ETL pipelines and working with job-scheduling systems
• Extensive experience with cloud platforms (e.g., AWS, GCP, Azure) and managing large-scale data processing
• Expertise in deploying ML models using modern tools (e.g., Docker, Kubernetes, CI/CD pipelines)
• Experience in causal inference and designing experiments is a plus
• Strong understanding of MLOps principles and tools to streamline model deployment and lifecycle management
• Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders

Do you like to learn hard, work hard and play hard?

Do you imagine better things, technologies, future?

If you answered “Yes” to at least two of these questions then we might be a great fit for you.