As a Machine Learning Engineer at MindPeers, you will help us build and deploy innovative models to enhance system understanding for the next million users. Your solutions will keep us ahead of the innovation curve, making mental health more accessible and trackable for our users.
Responsibilities
Conceptualize, analyze, build, test, and deploy models to optimize the understanding of issues and track user improvement
Contribute to product strategy and evolve MindPeers Underwriting into one of the most innovative algorithms in the industry
Effectively communicate experimental results to leadership and the rest of the team
Mentor and grow other software engineers, data scientists, and ML engineers across teams
Qualifications
Educational background in Computer Science, Statistics, Mathematics, or a related quantitative field
At least 2 years of professional industry experience in Machine Learning Engineering
Expertise in machine learning, deep learning, ethical data science, natural language processing (NLP), and statistical modeling
Strong communication and collaboration skills
Strong data visualization skills
Excellent coding, documentation, version control, and testing skills in Python
Proficiency in building unsupervised machine learning models
Proficiency in ML/DNN using scikit-learn, TensorFlow, PyTorch, or similar frameworks
Proficiency in numerical and scientific libraries such as NumPy, scikit-learn, and Pandas
Proficiency in working on Big Data systems. Experience with Spark, Airflow, Snowflake, or similar technologies
Proficiency in NoSQL/SQL with a deep understanding of database systems