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Flexible Machine Learning Jobs in Cairo, GA (NOW HIRING)

Pursuit Aerospace

Lead Data Scientist

Thomasville, GA · On-site

$144K - $198K/yr

... * 2+ years in SQL, Python, Machine learning modeling, and time-series analytics * Must be ... flexible spending accounts, EAP, paid time off, and company-paid holidays. The specific programs ...

All JobsMachine Learning JobsFlexible Machine Learning JobsFlexible Machine Learning Jobs in Cairo, GA

Flexible Machine Learning information

See Cairo, GA salary details

$17K

$28.5K

$58.8K

How much do flexible machine learning jobs pay per year?

As of Aug 1, 2026, the average yearly pay for flexible machine learning in Cairo, GA is $28,464.00, according to ZipRecruiter salary data. Most workers in this role earn between $21,700.00 and $30,700.00 per year, depending on experience, location, and employer.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation tools can handle some tasks, MLEs are essential for creating complex models, interpreting results, and ensuring ethical implementation. AI may automate certain routine aspects, but the role of MLEs remains critical for innovation and system optimization in AI development.

What is the difference between Flexible Machine Learning vs Data Scientist?

AspectFlexible Machine LearningData Scientist
CredentialsTypically requires knowledge of machine learning, programming, and data analysis; certifications like AWS, Google Cloud are commonRequires degrees in statistics, computer science, or related fields; certifications like Certified Data Scientist are beneficial
Work EnvironmentOften in tech companies, startups, or consulting firms; involves building adaptable ML modelsIn various industries including finance, healthcare, and tech; focuses on data analysis and insights
Industry UsageUsed in AI development, automation, and predictive modelingApplied in business analytics, research, and strategic decision-making

Flexible Machine Learning professionals focus on developing adaptable ML models across diverse applications, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but their primary focus and industry usage differ slightly.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working in high-demand industries or at large tech companies can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in competitive markets or executive-level roles.

Which 3 jobs will survive AI?

Flexible Machine Learning roles such as data scientists, machine learning engineers, and AI specialists are expected to persist as they require complex problem-solving, domain expertise, and ongoing adaptation that AI cannot fully replicate. These jobs often involve designing, implementing, and maintaining AI systems, which demand advanced skills in programming, statistics, and critical thinking. Continuous learning and proficiency with tools like Python, TensorFlow, or cloud platforms are essential for these roles to remain relevant.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact. Such salaries are rare and generally found in large tech companies or specialized AI firms.
What cities near Cairo, GA are hiring for Flexible Machine Learning jobs? Cities near Cairo, GA with the most Flexible Machine Learning job openings:
Flexible Machine Learning jobs near you

Senior Data Engineer ID75059

AgileEngine

Tallahassee, FL • On-site, Remote

$100K - $136K/yr

Full-time

Posted 29 days ago

Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you\'re looking for a place to grow, make an impact, and work with people who care, we\'d love to meet you!
ABOUT THE ROLE
We are looking for a Senior Data Engineer to design and build scalable data lakes, warehouses, and lakehouse architectures supporting a thematic research platform that processes large volumes of financial data daily. You will implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ingestion workflows from third-party APIs, and work with Snowflake, Spark, and AWS to deliver high-performance data infrastructure. The role combines hands-on engineering with technical consulting responsibilities, translating business goals into data architecture roadmaps.
WHAT YOU WILL DO
- Design and implement Python Data Engineering solutions;
- Design and build scalable Data Lakes, Data Warehouses, and Data Lakehouses;
- Design and implement robust ETL/ELT processes at scale using Python, incorporating modern pipeline orchestration tools like Airflow;
- Develop sophisticated ingestion workflows from diverse 3rd party APIs and data sources;
- Manage and optimize various file formats (Parquet, Avro, ORC) and columnar storage to ensure high-performance data retrieval;
- Work with AI development tools to support and accelerate ongoing development, machine learning initiatives and advanced analytics;
- Act as a technical consultant for stakeholders and leadership to gather requirements, understand business goals, and translate them into technical roadmaps;
- Work with Terraform and other tools to build AWS and on-prem infrastructure.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience;
- 5+ years of experience with Python (strong, hands-on Python experience is a must);
- 5+ years of experience with data processing, manipulation, and analytics libraries like Pandas, Polars, PySpark or DuckDB;
- 2+ years of experience with Big Data technologies (Spark, Snowflake);
- Expert-level knowledge of pipeline orchestration using Airflow or similar industry-standard tools;
- Deep understanding of Medallion Architecture, columnar file formats, and diverse database technologies (SQL, NoSQL, and Lakehouse architectures);
- Proven ability to work with 3rd party APIs for complex data ingestion tasks;
- Proficiency with modern Cloud platforms (AWS, GCP, Snowflake) and advanced SQL optimization;
- Exceptional soft skills with a proven ability to gather requirements from leadership and collaborate effectively across cross-functional teams;
- Excellence in optimizing complex data pipelines and troubleshooting data latency or consistency issues in massive datasets;
- A self-starter mindset, regularly investigating more efficient data architectures and AI development tools to improve pipeline performance;
- Taking pride in data integrity and the accuracy of the end-to-end pipelines and architectures you build;
- Strong communication skills for seamless global collaboration with stakeholders and distributed teams;
- Upper-intermediate English level.
NICE TO HAVES
- Familiarity with the fintech industry, understanding of financial data, regulatory requirements, and business processes specific to the domain;
- Documentation skills to document data pipelines, architecture designs, and best practices for knowledge sharing and future reference;
- OpenSearch, Elasticsearch;
- AWS Sagemaker Studio, Jupyter for analyze data;
- Terraform;
- Scala.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.

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