PhD Machine Learning Engineer [Contract - 6 months]

at  Cutting Edge Search

CORE SKILLS AND REQUIREMENTS:

• Computer Science Proficiency: Strong foundational knowledge in algorithms, data structures, machine learning, AI, and data processing.
• Problem-Solving Ability: Creativity and systematic thinking to address complex computational challenges, with a focus on efficiency.
• Technical Expertise: Experience with programming languages (e.g., Python, Java, C++) and data analysis/machine learning libraries (e.g., TensorFlow, PyTorch) along with big data frameworks (e.g., Hadoop, Spark).
• Research Skills: Ability to frame computational challenges as research questions, design experiments, and evaluate findings.
• Communication: Strong written and verbal skills for presenting technical concepts and research outcomes.

PREFERRED QUALIFICATIONS:

• PhD or Master’s degree in Computer Science or a related field, ideally with a focus on AI, machine learning, or data science.
• Proven research experience in AI or related areas, either in academia or industry.
• Experience with AI tools (e.g., TensorFlow, PyTorch) and familiarity with cloud computing platforms.
• Background in handling large-scale datasets, multi-modal data, and complex system architectures.

ROLE OVERVIEW:

A well-funded AI research and development company is looking for candidates with a strong foundation in Computer Science, especially in areas like artificial intelligence, machine learning, data science, and algorithms. The ideal candidate will have a high level of expertise in advanced computing concepts relevant to academic research or professional practice. In this role, you will work with diverse data types, including text, images, simulations, and structured datasets, so experience with various data formats and processing techniques is essential. The position requires solving complex computational problems, designing efficient algorithms, and contributing to a fast-paced research environment.

DAY-TO-DAY RESPONSIBILITIES:

In this role, you will tackle advanced computer science challenges in AI, machine learning, and data analysis, while developing innovative, research-driven solutions. Sample tasks include:

• Algorithm Development: Design and implement optimized algorithms for processing and analyzing large datasets, focusing on performance and scalability.
• AI Model Building: Develop machine learning models for tasks such as image recognition, natural language processing, and predictive analytics, using state-of-the-art research techniques.
• Data Integration & Visualization: Integrate data from structured and unstructured sources, generating clear visualizations and actionable insights.