Senior MLOps

Intellectsoft is a digital transformation consultancy that provides cutting edge engineering solutions for global organizations.

Our mission is to help enterprises accelerate adoption of new technologies, untangle complex issues that always emerge during digital evolution, and orchestrate ongoing innovation. Established in 2007, the company is headquartered in New York and operates in multiple offices and engineering centers in the US, the UK, the Nordic region and Eastern Europe.

Our main focus is on new and emerging technologies, such as Cognitive Computing, Decentralized Applications, and Internet-of-Things. Among our clients are globally recognized brand names, such as Universal Pictures, Jaguar Motors, Qualcomm, Ernst & Young, Clinique, Bombardier, London Stock Exchange, Harley-Davidson and many others.

For more information please visit our website www.intellectsoft.net.

Our customer is a leading consulting, software, and technology company servicing industries such as healthcare, private equity, technology, and more. It develops products that create value and deliver company results across critical areas of its business, including portfolio strategy, customer insights, research and development, operational and technology transformation, marketing strategy, and many more. Besides, the company is at the forefront of innovation, actively expanding its AI services to deliver cutting-edge solutions.

Requirements

• 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 skills

• Knowledge and experience in API development.

Responsibilities

• Develop, refine, and use ML engineering platforms and components.
• Ensure our programs can efficiently handle large volumes of data and meet deadlines.
• Establish and manage processes for models, including data preparation and prediction.
• Monitor model performance closely and address any issues promptly.
• Collaborate closely with client-facing teams to understand their needs and provide technical support.
• Translate client requirements into straightforward features.
• Write robust code that is easy to test, maintain, and troubleshoot.
• Maintain high standards by adhering to guidelines, participating in code reviews, and ensuring code quality.
• Thoroughly test all components to anticipate and resolve potential issues.
• Utilize tools for issue tracking, code review, and version control.
• Actively participate in team meetings to discuss progress and future plans.
• Stay updated on the latest developments in technology and explore innovative solutions.

Benefits

• 35 paid absence days per year for work-life balance of each specialist + 1 additional day for each following year of cooperation with the company
• Up to 15 unused absence days can be add to income after 12 month of cooperation
• Health insurance for you
• Depreciation coverage for personal laptop usage for project needs
• Udemy courses of your choice
• Regular soft-skills trainings
• Excellence Сenters meetups