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Machine Learning Engineer

2 months ago

Austin, Texas, United States Diversity Talent Scouts- Executive Search Firm Full time

**Job Opportunity**

We are seeking a highly skilled Machine Learning Engineer to contribute to the advancement of AI/ML integration and adoption across our organization. This role plays a pivotal part in driving innovation and excellence in machine learning, software engineering, and data science.

The ideal candidate will possess a strong foundation in machine learning, software engineering, and data science, along with a passion for tackling complex challenges and developing scalable systems. You will be involved in developing, deploying, and optimizing machine learning models while collaborating closely with cross-functional teams.

**Key Responsibilities**

  • Lead efforts to develop and implement a governance model for AI/ML and other analytics.
  • Design, develop, and deploy machine learning solutions, ensuring proficiency with SageMaker, AWS Glue, Copilot, Chat GPT, Open AI, and/or Microsoft AI technologies.
  • Measure and communicate the business impact of AI/ML initiatives and drive continuous improvement.
  • Analyze data and translate findings into actionable insights for end users.
  • Assess and monitor the performance of systems, ensuring compliance with standards and protection against cybersecurity threats.
  • Lead complex, data-driven research projects that influence business outcomes.
  • Develop and execute analytical solutions for diverse challenges.
  • Acquire, analyze, and act on complex datasets; create ETL jobs; explore, inspect, and clean data; engineer features.
  • Train, validate, test, deploy, and maintain machine learning models in production environments.
  • Organize and lead stakeholder meetings; collaborate with internal teams to achieve project goals.
  • Stay abreast of advancements in data science, statistics, machine learning, and AI.
  • Ensure machine learning models are scalable, reliable, and efficient; integrate models with existing systems and platforms; optimize model performance.
  • Document design specifications, processes, models, and systems to ensure transparency and reproducibility.

**Requirements**

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, Engineering, Mathematics, or a related field.
  • Minimum of 3 years of experience in machine learning, with exposure to software engineering best practices.
  • At least 2 years of hands-on experience with technologies such as SageMaker, AWS Glue, Copilot, Chat GPT, Open AI, and/or Microsoft AI technologies.
  • Proven experience in developing and deploying machine learning models in production environments.
  • Strong understanding of machine learning algorithms, data structures, and software design principles.

**Preferred Qualifications**

  • Proficiency in programming languages such as Python, Java, or C++.
  • Extensive experience with machine learning frameworks and libraries like TensorFlow, PyTorch, and Scikit-learn.
  • Solid understanding of software engineering principles, including version control (Git), testing, and CI/CD pipelines.
  • Strong skills in data preprocessing, feature engineering, and data analysis using tools like Pandas and NumPy.
  • Proficiency with platforms such as SageMaker, AWS Glue, Copilot, Chat GPT, Open AI, and/or Microsoft AI technologies.
  • Ability to quickly learn and work with new machine learning models, including Large Language Models (LLMs).
  • Experience with cloud platforms such as AWS, GCP, or Azure for deploying and managing machine learning models.
  • Expertise in designing, creating, and deploying AI and ML solutions.
  • Experience in analyzing business requirements, recommending, and designing technical solutions.
  • Strong technical writing skills to develop detailed design specifications and documentation.
  • Excellent analytical and problem-solving abilities, with a track record of handling complex projects and delivering impactful solutions.
  • Proficient in system security best practices.
  • Adaptability to shifting priorities, demands, and timelines with strong analytical and problem-solving capabilities.
  • Ability to work independently or collaboratively within a team-oriented environment.
  • Proactive, with strong time management, problem prevention, and problem-solving skills.

**Nice to Have**

  • In-depth knowledge of Large Language Models (LLMs), including architectures, training processes, and applications; experience with frameworks and tools such as GPT, BERT, or similar, and a deep understanding of fine-tuning techniques and deployment strategies.
  • Experience with deep learning architectures and techniques.
  • Familiarity with big data technologies such as Apache Spark, Hadoop, and Kafka.
  • Strong system design skills and experience in building large-scale distributed systems.
  • Experience with containerization (Docker) and orchestration (Kubernetes).
  • Knowledge of specific domains such as natural language processing, computer vision, or recommendation systems.
  • Strong project management and leadership abilities.