Join BeGig as a Machine Learning Engineer to help startups build intelligent systems that learn from data and drive business outcomes. You'll work on real-world use cases across recommendation engines, predictive analytics, personalization, and generative AI. As a freelancer, you'll be matched with high-impact opportunities tailored to your expertise.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
About BeGig
BeGig is the leading tech freelancing marketplace. We empower innovative, early-stage, non-tech founders to bring their visions to life by connecting them with top-tier freelance talent. By joining BeGig, you're not just taking on one role—you’re signing up for a platform that will continuously match you with high-impact opportunities tailored to your expertise.
Your Opportunity
Join our network as a Machine Learning Engineer and help startups build intelligent systems that learn from data and drive business outcomes. You'll work on real-world use cases across recommendation engines, predictive analytics, personalization, and generative AI—contributing to models that power scalable products.
Role Overview
As a Machine Learning Engineer, you will:
- Design, develop, and deploy machine learning models tailored to specific business needs
- Build end-to-end ML pipelines from data preprocessing to inference
- Collaborate with cross-functional teams to integrate models into production systems
What You’ll Do
- Train and evaluate models using frameworks like scikit-learn, XGBoost, PyTorch, or TensorFlow
- Handle data wrangling, feature engineering, and model optimization
- Set up automated ML workflows and performance monitoring
- Deploy models using APIs, cloud services, or containerized environments
- Continuously improve accuracy, scalability, and runtime efficiency
Technical Requirements
- 3+ years of experience in ML engineering or applied data science
- Proficient in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch
- Experience working with structured, unstructured, or time-series data
- Familiarity with cloud platforms (AWS, GCP, Azure) and model deployment tools
- Bonus: experience with MLOps tools like MLflow, Airflow, or Kubeflow
What We’re Looking For
- A problem-solving engineer who knows how to translate data into insights and actions
- A freelancer who can own ML components end-to-end and communicate clearly with stakeholders
- Someone who thrives in agile, product-focused startup environments
Why Join Us
- Build ML solutions that make a real impact on products and users
- Fully remote and flexible freelance opportunities
- Get matched with future ML roles across a range of industries and use cases
- Join a forward-looking network shaping the future of applied machine learning
Ready to turn data into intelligent action? Apply now to become a Machine Learning Engineer with BeGig.
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