
Machine Learning Engineer Role
1 week ago
We're looking for a talented professional to collaborate with our development and product teams, working on machine learning, deep learning, DevOps, and AI. As a junior Machine Learning Engineer, you will have the opportunity to work closely with our MLOps experts, learning how to create and fine-tune models from large amounts of raw information and optimize them.
You will be responsible for building ML/DL data pipelines to extract valuable business insights, analyze trends, and help us make better decisions. This requires being highly analytical with a knack for analysis, math, and statistics, as well as a passion for machine learning and research.
Critical thinking and problem-solving skills are essential for this role. You will need to research and analyze valuable data sources, perform preprocessing of structured and unstructured data, review large amounts of information to discover trends and patterns, create predictive models and machine-learning algorithms, modify and combine different models through ensemble modeling, and organize and present information using data visualization techniques.
Responsibilities:
- Extract insights from data to inform business decisions
- Develop and implement data processing and machine learning pipelines
- Analyze complex data sets to identify trends and patterns
- Create and deploy predictive models using machine learning algorithms
- Work collaboratively with cross-functional teams to achieve project goals
Requirements:
- No experience necessary, remote opportunity available
- Knowledge of SQL and Python; familiarity with Scala, Java, or C++ is a plus
- Familiarity with Kubernetes and/or containerization systems
- Strong analytical and mathematical skills, with business acumen
- Excellent communication and presentation skills
- Good problem-solving abilities
- BSc or BA degree in Computer Science, Engineering, or relevant field
About Us: We are a rapidly growing open-source MLOps platform that helps data science, ML engineering, and DevOps teams easily develop, orchestrate, and automate ML workflows at scale. Our frictionless, unified, end-to-end MLOps suite enables users and customers to focus on developing their ML code and automation, ensuring their work is reproducible and scalable.
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