Engineer machine learning engineer
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Job Overview The Machine Learning (ML) Engineer plays a pivotal role in advancing AI capabilities, focusing on the design, development, and deployment of machine learning models with an emphasis on large language models (LLMs) and state-of-the-art technologies. This position is essential for building scalable AI applications that deliver real-world impact, ensuring models are optimized for performance, reliability, and responsible use. Collaborating with various technical teams, they facilitate the seamless integration of LLM-powered applications into products and workflows. Their expertise ensures the organization remains at the forefront of AI innovation, reinforcing a culture of continuous improvement and leadership in applying advanced AI technologies. Job Responsibilities :- Build and maintain the entire machine learning lifecycle (research, design, experimentation, development, deployment, monitoring, and maintenance).
- Assemble large, complex data sets that meet functional/ non-functional business requirements for machine learning.
- Collaborate with data science, tech, and product teams on defining, architecting, and building data ingestion systems and model training pipelines from experimentation to deployment, monitoring, and continuous performance improvement.
- Design, develop, and deploy machine learning and large language models (LLMs) to power scalable AI applications.
- Fine-tune, optimize, and maintain AI models to ensure performance, reliability, and responsible use.
- Collaborate with cross-functional technical teams to integrate AI-driven solutions into products, platforms, and workflows.
- Conduct rigorous evaluations and benchmarking of AI models and applications to validate accuracy, efficiency, and trustworthiness.
- Research and apply emerging machine learning techniques and AI frameworks to advance innovation and maintain industry leadership.
- Build and maintain pipelines, tooling, and infrastructure for model training, deployment, and monitoring in production environments.
- Ensure scalability, security, and compliance of AI systems while aligning with business and operational requirements.
- Participate in other duties or projects as assigned by business management as needed.
- Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required)
- Master's/Advanced Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred)
- Data Engineering, Data Science (Required)
- Experience designing, developing, and deploying machine learning models and large language models (LLMs) in production environments (Required)
- Experience building and maintaining end-to-end ML pipelines including data ingestion, training, deployment, monitoring, and optimization (Required)
- Experience applying MLOps practices and cloud platforms (AWS, GCP, or Azure) for scalable AI solutions (Preferred)
- Experience implementing fine-tuning, evaluation, and benchmarking techniques for LLMs and generative AI applications (Preferred) Experience collaborating with cross-functional teams (engineering, data science, and product) to deliver AI-powered applications (Required)Experience in programming languages such as Python/R, Java/Scala, and/ or Go (Required)
- Experience in the telecom industry (Preferred)
- Proficiency in building and deploying machine learning models and algorithms (Required)
- Ability to identify, troubleshoot, and resolve complex technical issues (Required)
- Strong analytical and problem-solving abilities with attention to model performance, fairness, and responsible AI practices (Preferred)
- At least 18 years of age
- Legally authorized to work in the United States
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