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Machine Learning Engineer Software Engineer Jobs in Tennessee

... machine learning models and large language models. • Conduct research to provide technical ... and software engineering, focusing on continuous improvement and feedback mechanisms. • ...

As a Software Engineer, you will be a core contributor to Verint's QM and PM engineering team. You will design and build full-stack features end-to-end, write high-quality automated tests, support ...

Embedded Software Engineer

La Vergne, TN · On-site

$124K - $164K/yr

Nashville, TN At Coats, we design, build, and support the technologies and machines that keep ... We are hiring a mid-level Software Engineer (Engineer II) to design, develop, and maintain software ...

Embedded Software Engineer

La Vergne, TN · On-site

$124K - $164K/yr

Nashville, TN At Coats, we design, build, and support the technologies and machines that keep ... We are hiring a mid-level Software Engineer (Engineer II) to design, develop, and maintain software ...

AI/ML Engineer RFP Radar

Franklin, TN

$103K - $141K/yr

Applied Machine Learning: Practical experience integrating Machine Learning into production software workflows. You don't need to be a research scientist, but you must know how to apply standard ML ...

AI/ML Engineer RFP Radar

Franklin, TN · On-site

$103K - $141K/yr

Applied Machine Learning: Practical experience integrating Machine Learning into production software workflows. You don't need to be a research scientist, but you must know how to apply standard ML ...

Unified Enterprises Corp. seeks candidates for the position of Software Engineer, responsible for the full software lifecycle development from design, development and testing, all the way through ...

Unified Enterprises Corp. seeks candidates for the position of Software Engineer, responsible for the full software lifecycle development from design, development and testing, all the way through ...

Sr. Engineer, Software

Nashville, TN

$118K - $156K/yr

As a Senior Software Engineer, you will take deep technical ownership of significant product features and subsystems within Verint's QM and PM platform. You will lead the design and implementation of ...

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Machine Learning Engineer Software Engineer information

What is the difference between Machine Learning Engineer Software Engineer vs Data Scientist?

AspectMachine Learning EngineerSoftware Engineer
Required CredentialsBachelor's/Master's in CS, specialized ML coursesBachelor's in CS or related field
Work EnvironmentDevelops ML models, algorithms, data pipelinesBuilds software applications, systems, APIs
Industry UsageAI/ML projects, data-driven solutionsWeb, mobile, enterprise software

Machine Learning Engineers focus on designing and deploying ML models, requiring expertise in algorithms and data handling. Software Engineers develop broader software applications, emphasizing coding and system architecture. While both roles require programming skills, ML Engineers specialize in AI/ML tasks, whereas Software Engineers work across various software domains.

How do Machine Learning Engineer Software Engineers typically collaborate with data scientists and software development teams?

Machine Learning Engineer Software Engineers often serve as a bridge between data scientists and software development teams. They work closely with data scientists to understand and implement machine learning models, ensuring that the models are production-ready and scalable. Additionally, they collaborate with software engineers to integrate these models into existing applications, monitor their performance, and address any engineering challenges. This cross-functional collaboration is essential for delivering robust, end-to-end AI solutions that add real value to the business.
What job categories do people searching Machine Learning Engineer Software Engineer jobs in Tennessee look for? The top searched job categories for Machine Learning Engineer Software Engineer jobs in Tennessee are:
What cities in Tennessee are hiring for Machine Learning Engineer Software Engineer jobs? Cities in Tennessee with the most Machine Learning Engineer Software Engineer job openings:
AI Data Engineer - Manager

AI Data Engineer - Manager

Deloitte

Nashville, TN • On-site

Full-time

Posted 29 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

Job Summary:
Deloitte is a leading consulting firm focused on transforming the nature of work through innovative solutions. They are seeking an AI Data Engineer - Manager to lead data architecture and engineering delivery for AI/ML/GenAI solutions, ensuring data integrity and scalability while managing a team and collaborating with various stakeholders.
Responsibilities:
• Lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption.
• Design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data.
• Manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring.
• Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
• Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases.
• Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
• Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
• Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
• Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
• Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
• Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
• Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
• Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
• Be responsible for the successful execution of AI-powered applications using agile methodology.
• Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
• Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
• Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
• Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
• Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
• Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
• Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
• 6+ years of consulting experience leading delivery teams, including onshore and offshore team members
• 6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
• 5+ years of experience working in an AI environment
• 5+ years of experience translating requirements into client ready design documents
• 5+ years of experience in software application architecture analysis, design, and delivery
• 5+ years of experience executing full system development life cycle implementations
• Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.
Preferred:
• Advanced degrees such as Masters or PhD are preferred
• Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
• 5 + years of experience in Data Science, Statistics, and Machine Learning
• 5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
• 5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
• 5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
Company:
Deloitte drives progress. Our firms around the world help clients become leaders wherever they choose to compete. Founded in 2008, the company is headquartered in Arlington, USA, with a team of 10001+ employees. The company is currently Late Stage.

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