Machine Learning Operations Engineer

We are Intellectsoft - a digital transformation consultancy group and engineering company that delivers cutting-edge solutions for global organisations and technology startups. Since 2007, we have been helping companies and established brands reimagine their business through digitalization. We're looking for an exceptional Machine Learning Operations Engineer to join our team. Are you up for a challenge?

The Client:

Our client, a leading consulting firm, holds significant influence in the global healthcare sector. With partnerships spanning nearly every major pharmaceutical and healthcare entity, they operate extensively in research and development, commercialisation, supply chain management, and manufacturing. Essentially, their services encompass the entirety of the healthcare value chain.

The Project:

There is no code / low code platform for business clients, which already exists but is the one that is actively developed. This platform is designed to generate autonomous agents at scale. These agents can facilitate various productivity enhancements within enterprises, such as Q&A engines, basic data analysis, and improved writing techniques. Some of the examples of how this platform operates: it creates content very quickly and precisely (for instance, drug description), it helps define the needs of the target audience (for example, this is helpful for sales representatives of pharmaceutical companies), it offers search system (end-users can effortlessly locate information even without precise keyword inputs).

Requirements

Must have:

• A degree in Computer Science, Engineering, Mathematics, or a relevant field.
• Minimum 3 years of experience in deploying and managing ML models.
• Proficiency with ML Ops for assessing and monitoring model performance and scalability.
• Skilled in creating feature engineering processes, inference pipelines.
• Strong programming skills in Python.
• Experience with distributed computing frameworks like Spark (PySpark).
• Experience with ML platforms like or similar to Airflow or any other orchestration workflow framework (SageMaker, Kubeflow, MLFlow)
• Proficiency in deploying models on cloud platforms such as AWS, Azure, or GCP. Experience with Kubernetes would be a big plus. 
• Experience with DevOps concepts, CI/CD pipelines, and data security measures, along with expertise in cloud platform architecture.
• Hands-on experience in data engineering within Big Data ecosystems.
• Familiarity with machine learning and deep learning principles.
• Knowledge of fundamental computer science concepts including common data structures and algorithms.
• Ability to collaborate effectively with diverse teams.
• Excellent English language skills.

Nice to have: 

• Knowledge and experience in API development.

Benefits

• 36 paid absence days per year for the work-life balance of each specialist + 1 additional day for each following year of cooperation with the company

• Up to 10 unused absence days can be added to income after 12 months of cooperation
• Health insurance compensation
• Depreciation coverage for personal laptop usage for project needs
• Udemy courses of your choice
• Regular soft-skills training
• Excellence Сenters meetups