Senior Machine Learning Engineer

Infopulse, part of TietoEvry Create, is inviting a talented professional to join our project as a Senior Machine Learning Engineer. Our customer is one of the Big Four companies providing audit, tax, consulting, and financial advisory services.

This role offers an opportunity to work across domains including Hoteling/Office Operations, Social Networking, and Finance (Invoicing), contributing to impactful, integrated machine learning solutions.

Areas of Responsibility

• Business Problem Solving: identify and define business problems and convert them into machine learning or data science tasks, proposing effective solutions
• SDLC Automation: contribute to and design software development lifecycle (SDLC) automation, implementing CI/CD and MLOps best practices
• Model Development and Optimization: architect, develop, train, evaluate, and optimize machine learning models to ensure cost efficiency and effectiveness
• Production Scalability: ensure ML solutions are robust, reliable, and scalable for production environments with a focus on model inference and integration
• Architecture Design: lead the design of ML solution architectures from data extraction and preprocessing to model deployment
• Pipeline Management: oversee provisioning, monitoring, and management of ML pipelines, collaborating closely with DevOps to ensure seamless data flow and model performance
• Quality Assurance: establish QA processes for ML solutions, including data validation, model testing, and pipeline monitoring

Qualifications

• Machine Learning Expertise: strong foundation in machine learning algorithms and data science principles
• Experience with Production-Ready ML: demonstrated experience in end-to-end machine learning solutions, particularly in production environments
• Programming Skills: proficiency in Python, with experience in libraries such as Pandas, SciPy, scikit-learn, Matplotlib, and NumPy
• Data Analysis Skills: strong knowledge of data analysis and preprocessing techniques using industry-standard tools and libraries

Will be an Advantage

• MLOps Knowledge: experience with MLOps tools and frameworks for model deployment and lifecycle management
• Cloud Experience: familiarity with cloud environments and services (e.g., AWS, Azure, GCP) related to machine learning
• Big Data Skills: experience working with big data tools like Spark, Hadoop, or similar technologies
• Domain Knowledge: background in hoteling, social networking, or finance-related applications of machine learning

Personal Skills

• Analytical Thinking: ability to analyze complex problems and devise efficient, innovative solutions
• Collaboration: willingness to collaborate with cross-functional teams including Product, DevOps, Backend, and Design
• Leadership: capability of providing technical guidance and mentorship to encourage best practices and innovation within the team
• Adaptability: ability to quickly adapt to new challenges, evolving technologies, and varying project demands
• Attention to Detail: strong focus on producing high-quality, reliable solutions that meet production standards.