Position Overview We are looking for a talented and motivated Machine Learning Engineer to contribute to our advanced distributed learning research project. This is an opportunity to work at the forefront of machine learning technologies, exploring innovative approaches to distributed and federated learning systems.
Key Responsibilities:
- Develop and implement distributed machine learning algorithms
- Design and optimize federated learning architectures
- Conduct research on privacy-preserving machine learning techniques
- Collaborate with a global team of researchers and engineers
- Implement and test novel distributed learning approaches
- Develop robust evaluation frameworks for distributed ML models
- Create documentation and research papers detailing findings and methodologies
Required Qualifications:
- Advanced degree (PhD preferred) in Computer Science, Machine Learning, or related field
- Expert-level programming skills in Python
- Deep understanding of machine learning and distributed computing principles
- Extensive experience with:
- TensorFlow or PyTorch
- Distributed computing frameworks
- Cloud computing platforms
- Machine learning model optimization techniques
- Strong background in statistical modeling and algorithm design
- Proven track record of research or publications in distributed learning
- Excellent problem-solving and analytical skills
Preferred Skills:
- Experience with federated learning architectures
- Knowledge of privacy-preserving machine learning techniques
- Familiar with differential privacy concepts
- Experience in blockchain or decentralized computing technologies
- Understanding of edge computing and IoT machine learning applications
Research Focus Areas:
- Privacy-preserving distributed learning
- Efficient model aggregation techniques
- Cross-device and cross-silo federated learning
- Handling non-IID (non-independent and identically distributed) data challenges
- Reducing communication and computational overhead in distributed learning
Technical Requirements:
- Proficiency in:
- Python
- Distributed computing frameworks
- Machine learning libraries
- Cloud platforms (AWS, GCP, Azure)
- Ability to work with complex distributed systems
- Strong understanding of machine learning model architectures
Commitment and Expectations:
- This is a volunteer research position
- Flexible remote working arrangement
- Estimated time commitment: 10-20 hours per week
- Opportunity to contribute to cutting-edge AI research
- Potential for publication and conference presentations
- Networking opportunities with global AI researchers
Benefits:
- Cutting-edge research experience
- Opportunity to work on innovative AI technologies
- Collaboration with leading researchers
- Professional development
- Publication and presentation opportunities
- Potential pathway to future research collaborations
Application Process: Interested candidates should submit:
- Detailed CV/Resume
- Research statement
- Portfolio of relevant projects
- Links to published research or GitHub repositories
- References from academic or industry mentors
Our Commitment: Connektiv8 is an equal opportunity research collective. We value diversity, creativity, and innovative thinking. We are committed to creating an inclusive environment that encourages collaboration and breakthrough research.
Note: This is a volunteer position focused on advancing the field of distributed machine learning. While no monetary compensation is provided, the research experience and potential publications offer significant professional development opportunities.
Job Features
| Job Category | Engineers, Technical |