Machine Learning Engineer - Remote Work

at  Bairesdev

At BairesDev®, we’ve been leading the way in technology projects for over 15 years. We deliver cutting-edge solutions to giants like Google and the most innovative startups in Silicon Valley.
Our diverse 4,000+ team, composed of the world’s Top 1% of tech talent, works remotely on roles that drive significant impact worldwide.
When you apply for this position, you’re taking the first step in a process that goes beyond the ordinary. We aim to align your passions and skills with our vacancies, setting you on a path to exceptional career development and success.
Machine Learning Engineer at BairesDev
We are looking for an outstanding Machine Learning Engineer to join our team. This professional will use data and machine learning techniques to help the business automate and scale decision-making, mainly by producing advanced data analysis reports and data-based models to infer and predict patterns.

What You Will Do:

• Help to improve data literacy and the overall analytical environment across the company.
• Handle both structured and unstructured data using SQL and other programming languages.
• Perform advanced data analysis and report results.
• Tell the story behind data in a compelling manner for business people.
• Build predictive models and machine-learning algorithms.
• Combine models through ensemble modeling.
• Propose solutions and strategies to business challenges.
• Help to design and execute experiments for hypothesis testing.
• Participate actively in discussions and decisions regarding the whole Machile Learning / Data Science chapter.
• Collaborate with data product managers to build awesome data products.
• Work with management to prioritize business and information needs.
• Help to spread a data-driven mindset and to improve data literacy. Be a data evangelist.

Here’s what we are looking for:

• 3+ years of experience with Machine Learning, data science, IA, statistical, and other related areas.
• Proficiency with MySQL.
• Proficiency in Python, R, or another major programming language.
• Excellent communication skills, and capacity to collaborate and build relationships with non-technical users.
• Strong knowledge of probability and statistics, including experimental design, predictive modeling, optimization, and causal inference.
• Hands-on experience with machine learning, like regression classification, clustering, neural networks, feature selection, cross-validation, the curse of dimensionality, bias-variance tradeoff, model explainability, NLP, etc.

Desirable:

• Experience with people analytics or growth.
• Experience with data visualization tools.
• Good understanding of the engineering challenges to deploying machine learning systems to production.

How we make your work (and your life) easier:

• 100% remote work (from anywhere).
• Excellent compensation in USD or your local currency if preferred
• Hardware and software setup for you to work from home.
• Flexible hours: create your own schedule.
• Paid parental leaves, vacations, and national holidays.
• Innovative and multicultural work environment: collaborate and learn from the global Top 1% of talent.
• Supportive environment with mentorship, promotions, skill development, and diverse growth opportunities.

Join a global team where your unique talents can truly thrive

• Help to improve data literacy and the overall analytical environment across the company.
• Handle both structured and unstructured data using SQL and other programming languages.
• Perform advanced data analysis and report results.
• Tell the story behind data in a compelling manner for business people.
• Build predictive models and machine-learning algorithms.
• Combine models through ensemble modeling.
• Propose solutions and strategies to business challenges.
• Help to design and execute experiments for hypothesis testing.
• Participate actively in discussions and decisions regarding the whole Machile Learning / Data Science chapter.
• Collaborate with data product managers to build awesome data products.
• Work with management to prioritize business and information needs.
• Help to spread a data-driven mindset and to improve data literacy. Be a data evangelist