Machine Learning Engineer - PyTorch/Tensorflow

About BeGig :

BeGig is the leading tech freelancing marketplace, helping early-stage, non-tech founders bring their visions to life by connecting them with top-tier freelance talent.

By joining BeGig, youre not just taking on one role youre joining a platform that continuously matches 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.

From recommendation engines and predictive analytics to personalization and generative AI, youll work on real-world use cases that power scalable products.

Role Overview :

As a Machine Learning Engineer, you will :

- Design, develop, and deploy ML models tailored to business needs.

- Build end-to-end pipelines from data preprocessing to inference.

- Collaborate with cross-functional teams to integrate models into production systems.

What Youll Do :

- Train and evaluate models using scikit-learn, XGBoost, PyTorch, or TensorFlow.

- Perform data wrangling, feature engineering, and model optimization.

- Automate ML workflows and monitor performance.

- Deploy models via APIs, cloud services, or containerized environments.

- Continuously improve accuracy, scalability, and efficiency.

Technical Requirements :

- 3+ years of experience in ML engineering or applied data science.

- Strong Python skills; experience with scikit-learn, TensorFlow, or PyTorch.

- Hands-on experience with structured, unstructured, or time-series data.

- Familiarity with AWS, GCP, or Azure for ML deployment.

- Bonus : knowledge of MLOps tools such as MLflow, Airflow, or Kubeflow.

What Were Looking For :

- A problem-solver who can translate data into actionable insights.

- A freelancer comfortable owning ML components end-to-end.

- Someone who thrives in agile, product-driven startup environments.

Why Join Us :

- Work on impactful ML projects across industries.

- Enjoy fully remote and flexible freelance opportunities.

- Get matched with future ML roles in diverse use cases.

- Join a forward-looking network shaping the future of applied ML.