**Job Summary**
We are looking for an accomplished **Machine Learning Engineer** to join our dynamic team. This role plays a key part in advancing AI/ML integration and adoption across our organization. The ideal candidate will possess a solid foundation in machine learning, software engineering, and data science, along with a passion for tackling complex challenges and developing scalable systems.
In this role, you will be involved in developing, deploying, and optimizing machine learning models while collaborating closely with machine learning engineers, data engineers, software developers, and stakeholders. Your deep expertise in advanced analytics and AI/ML practices will be instrumental in enhancing customer experiences and optimizing business operations. You will also partner with business leaders to explore innovative opportunities and shape state-of-the-art applications. This role requires a strong understanding of AI/ML, business strategy, and change management, and the ability to thrive in a cross-functional environment.
**Responsibilities**
Include but are not limited to:
- Lead efforts to develop and implement a governance model for AI/ML and other analytics.
- Design, develop, and deploy machine learning solutions; ensure 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.
**Qualifications**
- 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.
**Required Skills**
- 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.
**Preferred Skills**
- 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.
