AI / Machine Learning Engineer

Corework Staffing

  • Atlanta, Georgia
  • 8 days ago

    Highlights

    Overview : We are seeking a highly skilled and innovative AI / Machine Learning Engineer to design, develop, and deploy machine learning models and AI-driven solutions that solve complex business problems. The AI/ML Engineer works closely with Data Scientists, Software Engineers, Product Teams, and Data Engineers to turn data into intelligent, production-ready systems.

    Numbers & Facts

    LocationAtlanta, Georgia

    Description

    Job Description

    Overview:

    We are seeking a highly skilled and innovative AI / Machine Learning Engineer to design, develop, and deploy machine learning models and AI-driven solutions that solve complex business problems. This role focuses on building scalable ML systems, training predictive models, and integrating AI capabilities into production environments.

    The AI/ML Engineer works closely with Data Scientists, Software Engineers, Product Teams, and Data Engineers to turn data into intelligent, production-ready systems.

    Key Responsibilities:

    • Machine Learning Model Development
    • Design, build, and train machine learning and deep learning models
    • Develop predictive, classification, recommendation, and NLP models
    • Perform feature engineering, data preprocessing, and dataset optimization
    • Evaluate model performance using appropriate metrics (accuracy, precision, recall, F1, AUC, etc.)
    • Fine-tune hyperparameters to improve model performance and efficiency

    AI System Development & Deployment (MLOps)

    • Deploy machine learning models into production environments
    • Build scalable ML pipelines and automated workflows
    • Implement model monitoring, versioning, and retraining systems
    • Integrate AI models into APIs, web apps, or enterprise systems
    • Optimize models for speed, scalability, and cost efficiency

    Data Handling & Engineering Collaboration

    • Work with structured and unstructured datasets (text, images, audio, video)
    • Collaborate with data engineers to build clean, reliable data pipelines
    • Ensure data quality, integrity, and preprocessing standards
    • Explore large datasets to extract patterns and insights

    Research & Innovation

    • Research and implement state-of-the-art AI/ML algorithms
    • Experiment with deep learning frameworks (CNNs, RNNs, Transformers, LLMs)
    • Stay updated with advancements in generative AI and large language models
    • Prototype AI solutions for business use cases

    Collaboration & Communication

    • Work closely with product managers and stakeholders to define AI solutions
    • Translate business problems into machine learning solutions
    • Communicate model performance and technical insights clearly
    • Support cross-functional teams in AI adoption

    Requirements:

    • Bachelor's or Master's degree in Computer Science, Data Science, AI, Mathematics, or related field
    • Strong knowledge of machine learning algorithms and statistical modeling
    • Proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch)
    • Experience with data processing tools (Pandas, NumPy, SQL)
    • Understanding of model deployment and MLOps concepts
    • Strong problem-solving and analytical skills
    • Experience working with large datasets
    • Preferred (Nice-to-Have):
    • Experience with deep learning, NLP, computer vision, or generative AI
    • Familiarity with cloud platforms (AWS, Azure, GCP)
    • Experience with Docker, Kubernetes, and CI/CD pipelines
    • Experience building LLM-based applications (GPT, BERT, LLaMA, etc.)
    • Knowledge of data engineering tools (Spark, Hadoop)
    • Contributions to open-source AI projects or research papers

    Reporting To:

    • Head of Data Science / AI Lead / Engineering Manager / CTO
    • Employment Type & Work Setup:
    • Full-time / Contract-based
    • Onsite / Hybrid / Remote (depending on company structure)
    • Tech-driven environments (startups, enterprise AI teams, SaaS companies)
    • Flexible hours in agile development teams
    • Work Environment & Conditions:
    • Software engineering and data-driven development environment
    • Agile, sprint-based product teams
    • High collaboration with engineering, product, and analytics teams
    • Focus on innovation, experimentation, and production scalability
    • Fast-paced, research-driven technical environment

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