AI / Machine Learning Engineer

Data Freelance Hub
Chicago, US
Hybrid

Why this role

Pace
Fast Paced
The fast-paced environment is evident from the need to continuously research and apply new AI/ML techniques and tools, indicating a dynamic and evolving work context.
Collaboration
High
The job description highlights the necessity to collaborate with product, engineering, and business teams, emphasizing a team-oriented work environment.
Autonomy
Medium
The role requires the ability to work independently, as seen in the need to design, develop, and deploy machine learning models without direct oversight.
Decision Impact
Team
Decisions made in this role can significantly impact the business, as evidenced by the requirement to train, evaluate, and optimize models using appropriate metrics and validation techniques.
Role Level
Individual Contributor
The complexity of the role is high, as it involves working with large datasets, implementing MLOps practices, and ensuring data quality and compliance standards.

Derived from job-description analysis by Serendipath's career intelligence engine.

Transferable backgrounds

  • Coming from Data Scientist at a tech company
    Python programming · Machine learning model deployment
    The experience in deploying machine learning models and proficiency in Python directly align with the job requirements.
  • Coming from Software Engineer in a startup
    Version control · API integration
    A background in software engineering, particularly with version control and API integration, provides a strong foundation for this role.

Skills & requirements

Required

PythonML LibrariesCloud PlatformsData Processing ToolsMachine Learning ConceptsModel DeploymentApisMicroservicesBackend IntegrationData StructuresAlgorithmsSoftware Engineering PrinciplesVersion Control Systems

Preferred

Llms And Prompt EngineeringMlops ToolsContainerizationReal-time Data Processing SystemsRecommendation SystemsNLPComputer VisionFeature EngineeringModel OptimizationDistributed Systems Architecture

Stack & domain

PythonTensorFlowPyTorchscikit-learnSQLPandasSparkAWSAzureGCPDockerKubernetesAirflowProblem-solvingAnalytical ThinkingIndependent WorkCross-functional TeamworkCommunicationOwnership MindsetAdaptabilityAi/mlData ProcessingMlopsDistributed ComputingApisBackend IntegrationData GovernanceCompliance

About the role

This role involves designing and deploying machine learning models for practical applications, requiring a candidate who excels in Python and has a solid grasp of ML libraries and cloud platforms, working in a hybrid remote setup in Chicago.

Original posting from Data Freelance Hub

⭐ - Featured Role | Apply direct with Data Freelance Hub

This role is for an AI / Machine Learning Engineer with a contract length of over 6 months, offering a pay rate of up to $140,000 per year. Requires strong proficiency in Python, experience with ML libraries, cloud platforms, and data processing tools. Hybrid remote in Chicago, IL.

United States

Hybrid remote location: Chicago, IL 60617

Pay: Up to $140,000.00 per year

Key Responsibilities Design, develop, and deploy machine learning models for real-world applications Build and maintain scalable data pipelines for structured and unstructured data Collaborate with product, engineering, and business teams to define AI-driven solutions Train, evaluate, and optimize models using appropriate metrics and validation techniques Implement and maintain MLOps practices for model deployment, monitoring, and retraining Work with large datasets using distributed computing frameworks Integrate models into production systems via APIs and services Ensure data quality, governance, and compliance standards are met Continuously research and apply new AI/ML techniques and tools Required Skills & Qualifications Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience with data processing tools (SQL, Pandas, Spark, etc.) Solid understanding of machine learning concepts (supervised, unsupervised, deep learning) Experience building and deploying models in production environments Familiarity with cloud platforms (AWS, Azure, or GCP) Knowledge of APIs, microservices, and backend integration Understanding of data structures, algorithms, and software engineering principles Experience with version control systems (e.g., Git) Preferred Qualifications Experience with LLMs (Large Language Models) and prompt engineering Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow) Familiarity with containerization (Docker, Kubernetes) Experience with real-time data processing systems Background in statistics, mathematics, or related technical fields Prior experience in AI product development or startup environments Nice-to-Have Experience working with recommendation systems, NLP, or computer vision Knowledge of feature engineering at scale Experience optimizing models for latency and performance Exposure to distributed systems architecture Soft Skills Strong problem-solving and analytical thinking Ability to work independently and in cross-functional teams Clear communication of technical concepts to non-technical stakeholders Ownership mindset and attention to detail Adaptability in fast-paced environments Benefits Flexible schedule Hybrid remote work in Chicago, IL 60617 Freelance data hiring powered by an engaged, trusted community — not a CV database.

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Source: Data Freelance Hub careers

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