AI,ML Engineer

About SproutsAI

SproutsAI is a fast-growing startup specializing in artificial intelligence and machine learning technologies. We build cutting-edge solutions that help businesses automate and optimize their processes across industries. Our mission is to deliver innovative, scalable, and impactful AI-powered products. At SproutsAI, we champion a culture of learning, experimentation, and collaboration — making it the perfect place for engineers passionate about AI,ML to thrive and grow.

What You’ll Do

• Design, develop, and deploy machine learning models to solve real-world business problems.
• Work with structured and unstructured data to build data pipelines, preprocess datasets, and conduct feature engineering.
• Collaborate with software engineers and product teams to integrate ML models into production-grade applications.
• Evaluate model performance using appropriate metrics and continuously improve models based on feedback and data evolution.
• Stay updated with the latest research and advancements in machine learning and deep learning.
• Optimize models for performance, scalability, and inference efficiency in production environments.

• Bachelor`s or Master`s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
• Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
• Strong understanding of core machine learning conceptssupervised,unsupervised learning, model evaluation, overfitting,underfitting, etc.
• Hands-on experience with data preprocessing, exploratory data analysis (EDA), and feature engineering.
• Familiarity with version control (Git), Jupyter Notebooks, and model deployment basics (APIs, Docker, etc.).

• Experience with deep learning, NLP, computer vision, or recommendation systems.
• Knowledge of big data tools and frameworks (Spark, Dask, Ray) or cloud ML platforms (AWS SageMaker, GCP AI Platform).
• Understanding of model interpretability, explainability (SHAP, LIME), and responsible AI practices.
• Exposure to MLOps, CI,CD for ML workflows, and model monitoring in production.
• Published work (papers, GitHub projects, blogs) or contributions to open-source ML tools is a strong plus.

• Opportunity to work on high-impact AI projects from concept to deployment.
• Learn from and collaborate with a talented, multidisciplinary team.
• Remote-first culture with flexibility and a strong focus on outcomes.
• Fast-paced startup environment with real ownership and growth potential.
• Competitive compensation, equity options, and clear learning paths.