Machine Learning Team Lead $$$$

We are seeking an experienced and talented Lead Machine Learning Engineer

Innovecs is a global digital transformation tech company with a presence in the US, the UK, the EU, Israel, Australia, and Ukraine. Specializing in software solutions, the Innovecs team has experience in Supply Chain, Healthtech, Software & Hightech, and Gaming.
For the fifth year in a row, Innovecs is included in the Inc. 5000 and recognized in IAOP’s ranking of the best global outsourcing service providers. Innovecs is featured in the Global Top 100 Inspiring Workplaces Ranking and won gold at the Employer Brand Management Awards.

Our value to you: 

• Flexible hours and remote-first mode
• Competitive compensation
• Complete Hardware/Software setup – anything you need for work
• Open-door culture, transparent communication, and top management at a handshake distance
• Health insurance, vacation, sick leaves, holidays, paid maternity/paternity leave
• Access to our learning & development center: workshops, webinars, training platform, and edutainment events
• Virtual team buildings and social activities 
          

If you feel like you’re the perfect match for this role, drop us your CV! 

There are no limitations, no barriers when the right people are on your way — apply for the vacancy and succeed with us!

Innovecs is an equal opportunity employer. All hiring decisions are based on professional qualifications, skills, and experience. We are committed to a transparent, merit-based recruitment process that prevents discrimination and ensures equal opportunities for all candidates. Reasonable accommodations are available upon request throughout the recruitment process to support accessibility and inclusion.

Requirements

• BSc degree in Computer Science, Data Science, Statistics, or a related field. A Master's degree is a plus,
• At least 5 years of relevant work experience in machine learning, data science, or a related field,
• At least 1–2 years of experience in a technical leadership, team lead, or mentoring capacity,
• Proficiency in Python and SQL/NoSQL (Cassandra, MongoDB) for quantitative analysis, modeling, and data manipulation,
• Knowledge of cloud technologies such as AWS Sage Maker and MLOps practices and tools (e.g., MLFlow, KubeFlow),
• Knowledge of basic data structures and algorithms and OOP,
• Experience with Big Data Analytics and tools (e.g., Elasticsearch, Spark, Airflow) for data analysis and visualization,
• Familiarity with model deployment, MLOps practices, and the lifecycle of machine learning models,
• Familiarity with model and application monitoring tools (e.g., Evidently.ai, NewRelic),
• Strong communication, leadership, problem-solving, and stakeholder management skills,
• Strong analytical skills and experience working with large volumes of data,
• A strong desire to continuously learn, improve, and stay updated with the latest technologies and trends in AI/ML,

• Upper Intermediate English level, with excellent communication skills to effectively collaborate with both technical and non-technical teams.

   

Responsibilities

• Lead and mentor a team of ML engineers, providing technical direction and supporting team growth,
• Own the end-to-end development and delivery of ML solutions, from problem framing and experimentation to production deployment and monitoring,
• Analyze large, complex data sets to translate them into actionable insights,
• Design and review ML architectures, data pipelines, and MLOps workflows,
• Perform the preparation and preprocessing of both structured and unstructured data to ensure model accuracy and effectiveness,
• Design, develop, implement, and test both descriptive and predictive ML models, focusing on quality, accuracy, and consistency,
• Convert data into meaningful insights and present information using advanced data visualization tools and techniques,
• Deploy models into production environments and be responsible for model management (MLOps),
• Ensure best practices in model development, deployment, observability, CI/CD, and production support.