Machine Learning Engineer focusing on modeling cancer cells and developing related tools. Collaborating with researchers and scientists to advance cancer treatment through ML.
About the role
- AI/ML Engineer developing solutions in artificial intelligence for HPE. Responsible for conducting research, designing AI solutions, and mentoring team members.
Responsibilities
- Responsible for conducting advanced research in AI and machine learning
- Tasked with designing and architecting AI solutions for complex problems
- Provides technical guidance and mentorship to junior team members
- Participate in technical discussions and provide thought leadership within the organization
- Collaborates closely with stakeholders to understand their requirements and translate them into technical solutions
- Responsible for driving continuous improvement and innovation in the organization's AI and machine learning practices
- Facilitates design review sessions for your projects
- Collaborates closely with the engineering manager and team lead to refine and iterating on design and implementation strategies
- Independently prepares and delivers detailed presentations and reports to stakeholders
Requirements
- Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline
- Typically, 4-7 years’ experience
- Deep understanding of machine learning algorithms, such as linear regression, decision trees, support vector machines, random forests, deep learning models (e.g., neural networks), and reinforcement learning
- Proficient in model selection, hyperparameter tuning, and evaluating model performance using appropriate metrics
- A strong foundation in mathematics and statistics
- In-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts
- Understanding and developing complex machine learning models and algorithms
- Proficiency in programming languages such as Python, R, or Java
- Experience developing production-level code and familiarity with software engineering best practices, version control systems (e.g., Git), and software development methodologies
- Advanced knowledge and experience in deep learning
- Understanding advanced neural network architectures (e.g., convolutional neural networks, recurrent neural networks, transformers) and advanced techniques such as transfer learning, generative models, and optimization algorithms for deep learning
- Actively staying updated with the latest AI and machine learning research advancements
- Must have excellent communication skills to collaborate with cross-functional teams and stakeholders effectively
- Possess strong problem-solving and critical thinking abilities to guide projects, make strategic decisions, and solve complex technical challenges.
Benefits
- Health & Wellbeing benefits that supports physical, financial and emotional wellbeing
- Personal & Professional Development programs catered to career goals
- Unconditional Inclusion and flexibility to manage work and personal needs
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