Job Description
Are you ready to define the future of technology?
Nexus Future Tech is seeking a visionary Senior AI/ML Engineer to lead our next-generation artificial intelligence initiatives. As we scale our operations to meet the demands of 2024 and beyond, we need a technical expert to design, deploy, and optimize cutting-edge machine learning models that power our core products.
In this role, you will bridge the gap between complex algorithms and real-world business applications. You will work closely with cross-functional teams of data scientists, software engineers, and product managers to deliver scalable solutions that drive efficiency and innovation.
Why Join Us?
• Competitive base salary ($160k - $240k)
• Comprehensive health and wellness benefits
• Equity and performance bonuses
• Remote-first culture with flexible working hours
Responsibilities
- Design & Development: Architect and implement scalable machine learning pipelines and deep learning models using Python, TensorFlow, and PyTorch.
- Model Optimization: Fine-tune existing models to improve accuracy, reduce latency, and optimize resource consumption for production environments.
- Data Strategy: Collaborate with data engineering teams to ensure high-quality data ingestion, cleaning, and feature engineering processes.
- MLOps Implementation: Establish and maintain CI/CD pipelines for machine learning models, ensuring automated testing and deployment.
- Research & Innovation: Stay abreast of the latest advancements in AI research and evaluate their applicability to our product roadmap.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: Minimum of 5 years of professional experience in machine learning, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, SQL, and experience with cloud platforms (AWS, GCP, or Azure).
- Frameworks: Strong hands-on experience with Scikit-learn, TensorFlow, Keras, or PyTorch.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and deliver robust engineering solutions.
- Communication: Excellent verbal and written communication skills with the ability to translate technical concepts to non-technical stakeholders.