About the Role
We are looking for a Machine Learning Engineer to join our team on a part-time, on-demand basis. This flexible role is ideal for a seasoned ML professional who wants to work on exciting projects and apply their expertise in designing, implementing, and optimizing machine learning solutions as needed.
What you’ll be doing:
- Develop, train, and optimize machine learning models for specific business requirements.
- Collaborate with stakeholders to define project goals and deliverables.
- Analyze data, perform feature engineering, and prepare datasets for model development.
- Evaluate and fine-tune existing models to improve performance and scalability.
- Deploy and integrate ML models into production systems.
- Stay up-to-date with the latest ML advancements and suggest innovative solutions.
- Provide technical consultation and recommendations on ML-related challenges.
What you’ll need:
- 5+ years of experience as a Machine Learning Engineer or Data Scientist.
- Proficiency in Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques.
- Experience with cloud platforms (AWS, Google Cloud, or Azure) for ML deployment.
- Familiarity with MLOps practices, including CI/CD pipelines for ML models.
- Solid understanding of statistics, linear algebra, and machine learning algorithms.
- Ability to work independently and communicate effectively with teams.
Nice-to-Have Skills:
- Experience with Computer Vision, NLP, or Reinforcement Learning.
- Knowledge of big data tools like Apache Spark or Hadoop.
- Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
- Background in working with startups or fast-paced environments.
We Offer:
- Flexible Schedule: Work on tasks as needed, with hours tailored to your availability.
- Exciting Projects: Contribute to diverse and impactful machine learning initiatives.
- Professional Growth: Collaborate with a skilled team and access opportunities for learning and innovation.
- Supportive Environment: Work remotely with a culture that values results, creativity, and collaboration.
If you’re an experienced ML Engineer seeking part-time work with the freedom to contribute on-demand, we’d love to hear from you! Apply now to be part of our team!