AI/ML Developers: Multiple Full-Time Roles
Zifcare
Full-time
On-site
United States
Development
Qualifications & Skills:
(a) Educational Background:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Relevant certifications or courses in AI/ML, Data Science, or related fields are a plus.
(b) Technical Skills:
- Programming Languages: Proficiency in Python, R, or similar languages used in AI/ML development.
- Machine Learning Frameworks: Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
- Data Handling: Strong skills in handling and processing large datasets, with proficiency in tools like Pandas, NumPy, and SQL.
- Model Development: Experience in developing, training, and deploying machine learning models, including supervised and unsupervised learning techniques.
- Algorithms: Understanding of fundamental AI/ML algorithms, including neural networks, decision trees, clustering, and regression.
- Deep Learning: Familiarity with CNNs, RNNs, LSTMs, GANs, and other deep learning architectures.
- Cloud Services: Experience with cloud platforms like AWS, Google Cloud, or Azure for AI/ML model deployment.
- Version Control: Proficient in using version control tools such as Git.
(c) Additional Skills:
- Problem-Solving: Strong analytical skills with the ability to solve complex problems using data-driven approaches.
- Communication: Effective communication skills to articulate technical concepts to non-technical stakeholders.
- Collaboration: Ability to work effectively in cross-functional teams, whether in-person or remotely.
- Adaptability: Willingness to learn and adapt to new technologies and methodologies in the AI/ML field.
(d) Experience Levels:
- Junior: 0-2 years of experience in AI/ML development or related fields.
- Mid-Level: 3-5 years of experience with a proven track record in AI/ML projects.
- Senior: 6+ years of experience, with leadership experience in AI/ML project management and model deployment.
Responsibilities:
(a) Model Development:
- Design, develop, and implement machine learning models and algorithms tailored to specific business needs.
- Continuously improve model performance by experimenting with different techniques and parameters.
(b) Data Analysis & Processing:
- Collect, clean, and preprocess large datasets from various sources to feed AI/ML models.
- Conduct exploratory data analysis to uncover trends, patterns, and insights.
(c) Deployment & Integration:
- Deploy and integrate AI/ML models into existing systems or new applications, ensuring scalability and reliability.
- Monitor model performance in production environments and implement improvements as needed.
(d) Collaboration & Communication:
- Collaborate with data engineers, software developers, and business analysts to translate business requirements into AI/ML solutions.
- Communicate findings and recommendations to stakeholders through reports, presentations, and visualizations.
(e) Research & Innovation:
- Stay updated with the latest advancements in AI/ML technologies and methodologies.
- Experiment with cutting-edge AI/ML tools and techniques to explore new opportunities for innovation.
(f) Documentation:
- Maintain comprehensive documentation of models, processes, and results to ensure reproducibility and knowledge sharing.
- Contribute to the development of best practices and standards for AI/ML development within the team.
(g) Mentorship (For Senior Roles):
- Provide guidance and mentorship to junior AI/ML developers, helping them to grow their technical skills and advance in their careers.
- Lead AI/ML projects and manage teams to ensure successful delivery of solutions.