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Science Engineering Jobs in Georgia (NOW HIRING)

Revenue Analytics

Data Scientist

Atlanta, GA · On-site

$95 - $110/hr

You will work on revenue management and pricing problems in a complex, fast-moving domain, partnering closely with product, science, and engineering to turn ambiguous questions into rigorous ...

Honeywell

Sr Advanced Data Scientist

Atlanta, GA · On-site

Master's degree in computer science, Engineering, Applied Mathematics or related STEM field * PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience with ...

Honeywell

Sr Advanced Data Scientist

Atlanta, GA · On-site +1

Master's degree in computer science, Engineering, Applied Mathematics or related STEM field * PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience with ...

Honeywell

Sr Advanced Data Scientist

Atlanta, GA · On-site +1

Master's degree in computer science, Engineering, Applied Mathematics or related STEM field * PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience with ...

Dlapiper

Director, Engineering

Atlanta, GA · On-site

Bachelor's Degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience. Preferred Education * Master's Degree in Technology, business, or ...

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Showing results 41-60

All JobsScience Engineering JobsScience Engineering Jobs in Georgia

Science Engineering information

See Georgia salary details

$34.2K

$83.4K

$132.1K

How much do science engineering jobs pay per year?

As of Aug 22, 2026, the average yearly pay for science engineering in Georgia is $83,390.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,900.00 and $97,900.00 per year, depending on experience, location, and employer.

What is a science engineer?

Science engineers are professionals who apply scientific principles and methods to design, develop, and improve technology, systems, or processes. They work at the intersection of science and engineering, often using their expertise to solve complex technical problems in fields such as materials science, biotechnology, environmental engineering, and more. Science engineers may conduct experiments, analyze data, and collaborate with scientists and other engineers to innovate new solutions. Their work is essential in advancing technology and addressing real-world challenges. Science engineers are found in research institutions, government agencies, and a wide range of industries.

What are the key skills and qualifications needed to thrive as a science engineer?

To thrive as a Science Engineer, you need a solid background in mathematics, scientific principles, and engineering fundamentals, typically supported by a relevant bachelor's degree or higher. Familiarity with industry-specific software, laboratory equipment, and certifications such as Professional Engineer (PE) licensure are often required. Strong problem-solving abilities, collaboration, and effective communication skills help Science Engineers excel in team-based environments and complex projects. These skills and qualities are crucial for developing innovative solutions, ensuring safety, and advancing scientific and engineering objectives.

How do science engineers typically collaborate with cross-functional teams on research and development projects?

Science engineers often work closely with professionals from various disciplines, such as chemists, physicists, software developers, and project managers, to drive innovation and problem-solving. Collaboration usually involves regular meetings to align on project goals, share research findings, and coordinate technical tasks. Effective communication and teamwork are essential, as science engineers must relay complex concepts in accessible terms and integrate feedback from different perspectives. This collaborative environment not only fosters creative solutions but also provides opportunities for professional growth and learning from peers in related fields.

What is the difference between Science Engineering vs Mechanical Engineering?

AspectScience EngineeringMechanical Engineering
Required CredentialsBachelor's or higher in Science Engineering or related fieldsBachelor's or higher in Mechanical Engineering
Work EnvironmentResearch labs, development centers, academiaManufacturing, design firms, industrial settings
Industry UsageResearch, product development, scientific analysisDesign, testing, manufacturing of mechanical systems

Science Engineering focuses on applying scientific principles to research and development, often in labs or academic settings. Mechanical Engineering emphasizes designing and manufacturing mechanical systems in industrial environments. While both require strong technical skills, their work environments and primary goals differ significantly.

What are science engineering jobs?

Science engineering jobs involve applying scientific principles and engineering techniques to develop, design, and improve systems, products, or processes. These roles often require knowledge of mathematics, physics, and specialized tools or software, and may include positions such as research engineers, systems engineers, or technical specialists in various industries.

What jobs can you get with a science engineering degree?

A science engineering degree can lead to careers such as mechanical engineer, electrical engineer, civil engineer, chemical engineer, or systems analyst. These roles typically require strong problem-solving skills, knowledge of engineering principles, and proficiency with tools like CAD software or laboratory equipment. Job opportunities are available in industries including manufacturing, construction, energy, and technology.

What are popular job titles related to Science Engineering jobs in Georgia?

For Science Engineering jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Science Engineering jobs in Georgia look for?

The top searched job categories for Science Engineering jobs in Georgia are:

What cities in Georgia are hiring for Science Engineering jobs?

Cities in Georgia with the most Science Engineering job openings:

Science Engineering jobs near you
Infographic showing various Science Engineering job openings in Georgia as of August 2026, with employment types broken down into 84% Full Time, 6% Part Time, 7% Contract, and 3% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $83,390 per year, or $40.1 per hour.

Staff, Data Science & Applied AI

Warner Bros. Discovery

Atlanta, GA • On-site

Full-time

Re-posted 13 hours ago

Warner Bros. Discovery rating

8.1

Company rating: 8.1 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

20th of 78 rated media

Job description

Welcome to Warner Bros. Discovery... the stuff dreams are made of.
Who We Are...
When we say, "the stuff dreams are made of," we're not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD's vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what's next...
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.
Your New Role:
As Staff, Data Science & Applied AI, you will be a core technical contributor within the Enterprise Data & AI Solutions team supporting Warner Bros. Discovery's global portfolio - including Studios, Streaming, Linear Networks, Consumer Products, Games, and Direct-to-Consumer platforms.
This role is designed for a hands-on expert in applied data science who thrives at the intersection of statistical rigor, machine learning engineering, and business impact. You will translate complex business challenges into scalable analytical solutions, production-grade models, and data products that drive measurable enterprise value.
You will operate as a senior individual contributor, partnering closely with Product, Engineering, and Business stakeholders to design, develop, deploy, and scale advanced analytics and AI capabilities across the organization.
Key Responsibilities include:
Advanced Analytics & Machine Learning
  • Design, develop, and deploy statistical, predictive, and machine learning models across domains such as customer analytics, forecasting, personalization, optimization, and content performance.
  • Apply advanced techniques including ensemble methods, gradient boosting, deep learning, NLP, time-series forecasting, and recommendation systems.
  • Ensure model robustness through rigorous validation, monitoring, and performance tracking.

Generative AI & LLM Applications
  • Design and implement Generative AI solutions leveraging large language models (LLMs) for use cases such as knowledge retrieval, content intelligence, metadata enrichment, summarization, and workflow automation.
  • Develop and optimize prompt engineering strategies, evaluation frameworks, and guardrails to ensure high-quality, reliable outputs.
  • Architect Retrieval-Augmented Generation (RAG) pipelines integrating structured and unstructured enterprise data sources.
  • Fine-tune or adapt foundation models where appropriate using parameter-efficient techniques (e.g., LoRA, adapters) aligned with business needs.
  • Implement evaluation pipelines to measure hallucination rates, bias, latency, cost efficiency, and model quality in production environments.
  • Collaborate with Responsible AI and Governance teams to ensure compliance with enterprise AI policies, data privacy standards, and ethical AI practices.

Product Ionization & AI Engineering
  • Collaborate with Data Engineering and DevOps teams to productionize ML and GenAI solutions in scalable cloud environments.
  • Design CI/CD pipelines for model lifecycle management, including experimentation tracking, versioning, and automated retraining.
  • Implement monitoring frameworks for model drift, prompt drift, performance degradation, and data integrity.

Automation & AI Framework Development
  • Develop reusable ML and GenAI frameworks, accelerators, and internal utilities that improve productivity across teams.
  • Advance automation initiatives to reduce manual workflows and enhance analytical velocity.
  • Stay current with cutting-edge advancements in foundation models, multimodal AI, and agentic architectures to continuously elevate enterprise AI capabilities.

Qualifications & Experiences:
  • Bachelor's degree, MS, or greater in Computer/Data Science, Engineering, Mathematics, Statistics, or related quantitative discipline.
  • 8+ years relevant experience in data science, 2+experience in GenAI
  • Demonstrated track record of delivering production-grade AI/ ML solutions with measurable business impact.

Generative AI & Large Language Model (LLM) Expertise
  • Hands-on experience designing and deploying Generative AI solutions using large language models (e.g., GPT-class models, open-source foundation models, or enterprise LLM platforms).
  • Strong proficiency in prompt engineering, structured output design, few-shot learning strategies, and systematic prompt optimization
  • Experience building Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and enterprise data sources.
  • Familiarity with embedding models, semantic search, and vector stores (e.g., Pinecone, Weaviate, OpenSearch, FAISS, or equivalent).
  • Experience fine-tuning or adapting foundation models using parameter-efficient approaches (e.g., LoRA, adapters, instruction tuning).
  • Understanding of LLM evaluation methodologies, including hallucination detection, bias assessment, response quality scoring, and cost-performance trade-offs.
  • Exposure to multimodal AI (text, image, audio, video) and agent-based workflows is a plus.
  • Experience working with enterprise AI platforms (e.g., AWS Bedrock, Azure OpenAI, Databricks Model Serving, Snowflake Cortex, or equivalent).
  • Understanding of Responsible AI principles, data privacy considerations, and model governance requirements in regulated environments.

How We Get Things Done...
This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.
Championing Inclusion at WBD
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law.
If you're a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

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