Senior AI Engineer

Skyworks-posted 9 months ago

$89,100 - $172,100/Yr

Full-time • Mid Level

Irvine, CA

Computer and Electronic Product Manufacturing

Resume

Match Score

Upload and Match ResumeTrack Jobs with Teal

The Enterprise AI Engineer position will be responsible for designing and implementing solutions that meet the needs of various business areas across Skyworks' Enterprise in and around the Machine Learning space. The incumbent will work under senior architects in the Enterprise Architecture group and with different departments to determine how to best implement new technologies and improve existing ones with a focus on machine learning operations and cloud platforms. Projects will be exciting and on modern platforms varying across ML/AI as well as data governance.

Partner with business stakeholders, data scientists, software engineers, and cross-functional teams to gather requirements and align machine learning and GenAI projects with strategic business objectives.
Develop solutions that seamlessly integrate with existing enterprise systems, databases, and APIs.
Design, develop, and fine-tune traditional machine learning models and large language models (LLMs) such as GPT, BERT, and other GenAI frameworks.
Apply state-of-the-art NLP techniques including text preprocessing, tokenization, named entity recognition (NER), sentiment analysis, text classification, and language generation.
Implement and optimize traditional machine learning techniques such as supervised and unsupervised learning, regression, classification, clustering, and ensemble methods.
Identify and address potential risks and challenges related to machine learning and GenAI, including data privacy, security vulnerabilities, and ethical considerations.
Continuously assess and enhance machine learning and GenAI models to improve accuracy, efficiency, and scalability.
Design and maintain data pipelines for sourcing and processing datasets required for training traditional ML, NLP, and GenAI models.
Deploy traditional machine learning, NLP, and GenAI models into production environments using platforms such as Azure Machine Learning Studio, Azure Kubernetes, and on-prem Kubernetes.
Architect and optimize inference pipelines, including data storage, data movement, compute instances, and networking.
Stay abreast of the latest research and advancements in machine learning, NLP, and GenAI.

BS Degree and 5+ years of experience.
Proficient in Python, with knowledge of C# and Java, and familiarity with scripting languages and tools such as Bash and PowerShell.
Strong knowledge of machine learning concepts, frameworks, and technologies, such as TensorFlow, PyTorch, Scikit-learn, SciPy, NumPy, Pandas, Hugging Face Transformers, and OpenAI.
Proficiency in advanced NLP techniques including text preprocessing, tokenization, named entity recognition (NER), sentiment analysis, text classification, and language generation.
Experience fine-tuning large language models (LLMs) such as GPT, BERT, and other GenAI frameworks.
Experience with traditional machine learning techniques such as supervised and unsupervised learning, regression, classification, clustering, and ensemble methods.
Experience with MLOps tools and practices, such as CI/CD, Docker, Kubernetes, and MLflow.
Experience with SQL and NoSQL databases, such as MSSQL and PostgreSQL.
Proficiency in designing and deploying machine learning models in cloud environments (e.g., Azure/Azure ML, AWS, GCP, AKS, and Kubernetes).
Demonstrated expertise in architecting scalable and secure machine learning infrastructure, including data pipelines, storage systems, and model deployment frameworks.
Excellent communication and collaboration skills, with the ability to effectively engage with stakeholders at various levels of the organization.
Ability to multitask and manage multiple activities simultaneously.
Ability to use a wide degree of creativity and latitude to think differently, challenge conventional wisdom, and drive new best practices.
Ability to work effectively with international teams.
Commitment to promoting ethical AI practices and ensuring transparency, accountability, and fairness in AI model development and deployment.
Strong problem-solving skills and the ability to adapt to rapidly changing technological landscapes.

Participation in research and development (R D) activities to explore innovative AI techniques and their potential applications.

Access to healthcare benefits (including a premium-free medical plan option).
401(k) plan and company match.
Employee stock purchase plan.
Paid time off (including vacation, sick/wellness, parental leave).
Eligibility to participate in an incentive plan.
Potential for additional awards, including recognition and stock based on individual and/or company performance.

Track Jobs with Teal

Job Search Resources

•

AI Resume Builder

•

AI Engineer Resume Examples

•

AI Engineer Cover Letter Examples

Senior AI Engineer

Job Search Resources

Tools

Career Hubs

Guides

Company