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Machine Learning Ai Developer information
What is the difference between Machine Learning Ai Developer vs Data Scientist?
| Aspect | Machine Learning Ai Developer | Data Scientist |
|---|---|---|
| Credentials | Bachelor's or higher in CS, AI, or related fields; certifications in ML/AI | Bachelor's or higher in CS, Statistics, or related fields; certifications in data analysis or ML |
| Work Environment | Develops AI models, algorithms, and applications; often in tech companies or R&D | Analyzes data, builds models, and provides insights; in various industries including finance, healthcare |
| Industry Usage | Primarily in AI product development, software, and tech firms | Across industries for data analysis, business intelligence, and decision-making |
While both roles require knowledge of machine learning and programming, Machine Learning Ai Developers focus on creating and deploying AI models and applications, whereas Data Scientists analyze data to extract insights and inform business strategies. The roles often overlap but differ in primary focus and application.
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Job description
A leading technology-driven organization in the industrial services and infrastructure sector is seeking a Manager to lead the next generation of AI and machine learning innovation. This role combines people leadership, technical strategy, and hands-on oversight of enterprise-scale machine learning initiatives that influence operational performance, intelligent automation, forecasting, and decision-making across the business.
You'll lead a team of experienced ML scientists and engineers while partnering with senior stakeholders to identify opportunities where predictive and generative AI can create measurable value. Working across modern cloud data platforms, MLOps ecosystems, deep learning frameworks, and large language model technologies, you'll play a key role in shaping both the organization's AI roadmap and its delivery capabilities.
- Proven experience leading machine learning teams while delivering production-grade AI and ML solutions at enterprise scale.
- Strong expertise in Python, SQL, machine learning frameworks (PyTorch, TensorFlow, scikit-learn), and modern MLOps practices including MLflow, model monitoring, and deployment automation.
- Experience building and operationalizing machine learning solutions within cloud and containerized environments using technologies such as Kubernetes, Docker, Git, APIs, and large-scale data platforms.
- Experience developing solutions leveraging large language models (LLMs), transformer architectures, multimodal AI, or other generative AI technologies.
- Knowledge of optimization, simulation, decision science, forecasting, or advanced statistical methodologies such as Bayesian inference.
- Experience building business-facing analytical applications and model visualization tools using React, Streamlit, or similar frameworks.
- Hands-On Engineering: 70%
- Team Collaboration & Cross-Functional Work: 30%
Applicants must be currently authorized to work in United States on a full-time basis now and in the future.
Accommodation will be provided in all parts of the hiring process as required under Motion Recruitment’s Employment Accommodation policy. Applicants need to make their needs known in advance.
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About Motion Recruitment
Sourced by ZipRecruiter
Industry
Recruiting and staffing services
Company size
501 - 1,000 Employees
Headquarters location
Boston, MA, US
Year founded
1989