Senior Machine Learning Engineer
2 weeks ago
Role: Senior Machine Learning Engineer
Location: Fort Mill, SC
Mode of Hire: Full Time
Responsibilities:
- Lead AI Strategy and Roadmap: Define the AI strategy, aligning it with business goals, and identify key areas where AI can create value for the organization.
- Oversee AI Solution Development: Guide the development and implementation of AI models, including machine learning, NLP, computer vision, and predictive analytics, ensuring solutions are robust, scalable, and aligned with requirements.
- Collaborate with Cross-Functional Teams: Work closely with product managers, data engineers, and software developers to integrate AI solutions into products and services.
- Ensure Model Quality and Accuracy: Establish best practices for model development, testing, and validation to ensure high-quality AI solutions, with a focus on accuracy, reliability, and bias mitigation.
- Data Management and Pre-processing: Oversee data sourcing, pre-processing, and feature engineering to ensure the quality and readiness of data used for AI models.
Skills Required:
- Experience: 3+ years of experience in AI, machine learning, or data science, with a proven track record of deploying AI solutions in a production environment.
- Technical Expertise: Deep understanding of AI and machine learning techniques, including supervised and unsupervised learning, NLP, computer vision, deep learning, and statistical modeling.
- Proficiency in AI Tools and Frameworks: Strong experience with AI and machine learning frameworks such as TensorFlow, PyTorch, Scikit-Learn, and cloud-based ML services (e.g., AWS SageMaker, Azure ML, Google AI).
- Programming Skills: Proficiency in programming languages like Python and familiarity with data processing libraries (e.g., Pandas, NumPy).
- Data Management Knowledge: Experience with big data technologies (e.g., Hadoop, Spark) and data engineering best practices.
- Strategic and Analytical Thinking: Ability to develop AI strategies aligned with business goals and assess the business impact of AI initiatives.
- Communication and Collaboration: Excellent communication skills to work effectively with cross-functional teams and to present complex technical information to non-technical stakeholders.
Preferred Skills:
- Knowledge of AI ethics, governance, and regulatory considerations.
- Experience with MLOps practices and tools for continuous integration/continuous deployment (CI/CD) of AI models.
- Advanced degree (Master's or Ph.D.) in computer science, AI, machine learning, or a related field.
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