Machine Learning Engineer

6 hours ago

Austin, United States Daman Full time

Job Title: Artificial Intelligence/Machine Learning Engineer

Location: Hybrid - Austin, TX (2 days a week onsite)

Role type: 12 Months contract


Job Overview


We are seeking a talented and innovative AI / Machine Learning Engineer to join our team. As part of the AI Technical Team, you will design, build, and deploy advanced machine learning models and AI solutions to solve real-world problems. You will work with large datasets, AI/ML frameworks, and cross-functional teams to deliver impactful results that align with our business goals.

If you are passionate about machine learning, artificial intelligence, and creating high-performance models, we’d love to hear from you.


Key Responsibilities

  • Model Development and Design: Develop, test, and optimize machine learning models for classification, regression, clustering, or recommendation tasks.
  • Data Preparation: work alongside the Enterprise Data Management Team to collect, clean, preprocess, and analyze large datasets to create high-quality training datasets.
  • Algorithm Implementation: Implement machine learning algorithms and neural networks using frameworks like TensorFlow, PyTorch, and scikit-learn.
  • Deployment and Integration: Deploy trained models into production environments using APIs, containers (e.g., Docker), or cloud services (AWS, GCP, or Azure).
  • Performance Monitoring: Monitor model performance, detect drift, and implement improvements or retraining strategies to ensure models remain accurate over time.
  • Collaboration: Work closely with our data management team, applications team, enterprise architects, and product managers to align solutions with business needs.
  • Documentation: Create thorough documentation for models, processes, and experiments to ensure reproducibility and scalability.
  • MLOps Practices: Develop automated pipelines for continuous integration, delivery, and model retraining (CI/CD).
  • Ethics and Compliance: Ensure AI models comply with industry regulations, address biases, and adhere to ethical standards.


Required Skills & Qualifications


  • Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
  • Programming Skills: Proficiency in Python, R, or similar programming languages.
  • Machine Learning Frameworks: Experience with TensorFlow, PyTorch, Keras, or scikit-learn.
  • Data Handling: Strong understanding of SQL, NoSQL, and big data tools (e.g., Spark, Hadoop).
  • Cloud Platforms: Familiarity with AWS, Google Cloud, or Microsoft Azure for deploying ML models.
  • Model Evaluation: Expertise in using metrics like accuracy, precision, recall, RMSE, or AUC-ROC for performance evaluation.
  • Version Control: Experience with GitHub, GitLab, or other version control tools.
  • Problem Solving: Strong analytical and problem-solving skills.
  • Communication: Ability to explain complex AI/ML concepts to non-technical stakeholders.

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