Senior Machine Learning Engineer

We are a startup on a mission to redefine social media through innovative technology. Our platform leverages cutting-edge AI to offer personalized experiences, real-time engagement, and intelligent content recommendations. We are seeking a Senior Machine Learning Engineer to join our team and spearhead the Artificial Intelligence and Machine Learning capabilities of the firm. As a key member of the technology team, you will play a pivotal role in advancing the firm's ML and AI capability within and not limited to deep learning, reinforcement learning, and generative AI as well as be at the forefront of MVP development.

Key Responsibilities

• Design, train, and fine-tune large language models (LLMs) and advanced deep learning architectures for various applications and be able to deploy these applications.
• Develop and implement reinforcement learning algorithms for real-world problem-solving in real time scenarios.
• Deploy machine learning models to production using AWS services specifically (expert knowledge of Sagemaker is a must).
• Build scalable and automated MLOps pipelines for CI/CD, monitoring, and retraining of models within AWS Sagemaker.
• Collaborate with data engineers to ensure clean and robust data pipelines.
• Stay up-to-date with the latest advancements in AI/ML research and apply them to innovative solutions.
• Optimize models for performance, scalability, and cost-efficiency.
• Mentor junior engineers and contribute to fostering a culture of innovation and technical excellence.

Qualifications

• Experience: Minimum of 10 years of experience in AI/ML, with a strong track record of delivering production-grade solutions.
• Expertise in LLMs: Hands-on experience in building, fine-tuning, and deploying large language models.
• Deep Learning: Proficiency in frameworks such as TensorFlow, PyTorch, and Keras.
• Reinforcement Learning: Solid experience implementing RL algorithms (e.g., DQN, PPO, A3C) in production.
• Cloud Expertise: Extensive experience with AWS services (e.g., SageMaker, S3, Lambda, ECS/EKS, DynamoDB).
• MLOps: Strong knowledge of MLOps practices, including CI/CD pipelines, model versioning, and monitoring tools.
• Programming Skills: Advanced proficiency in Python and familiarity with other languages like Java or C++ is a plus.
• Data Engineering: Experience with data preprocessing, feature engineering, and handling large datasets.
• Education: A degree in Computer Science, Data Science, Machine Learning, or a related field. A master’s or PhD is preferred.

Preferred Skills

• Familiarity with Deep Learning, Reinforcement Learning, and Generative AI.
• Experience with AutoML frameworks and hyperparameter optimization tools.
• Strong understanding of distributed systems and parallel computing for large-scale training.
• Knowledge of ethical AI practices and model explainability techniques.
• AWS Cloud Expert as it pertains to using Sagemaker.

Benefits:

• Equity Stake.
• The opportunity to shape the technical backbone of a revolutionary product from the ground up.
• A vibrant, growth-oriented culture that values innovation and collaboration.

Join us if you are ready to challenge conventions, inspire others, and make your mark on the future.