Senior Machine Learning Engineer

About Us:

At Alkye, we are at the forefront of the digital and technology industry, creating innovative solutions that drive business success. Our team is passionate about leveraging the power of Machine Learning and Generative AI to solve complex problems and enhance our product offerings. We are looking for a dedicated and talented Senior Machine Learning Engineer to join our dynamic team. If you have a passion for Generative AI, and machine learning innovations, and are eager to lead transformative projects, we want to hear from you!

Job Summary:

As a Senior Machine Learning Engineer at Alkye, you will lead efforts to develop, deploy, and optimize advanced ML and Generative AI models, including LLMs, image generation, and multi-modal systems. You will collaborate with cross-functional teams to bring machine learning prototypes into production, ensuring they are scalable, efficient, and integrated seamlessly with our systems. This role requires deep knowledge of data science, deep learning, and Generative AI, as well as strong MLOps expertise.

Key Responsibilities:

• Model Development and Deployment: Design, develop, and deploy advanced machine learning models (including Generative AI models, LLMs, and multi-modal architectures) to solve complex business challenges and enhance user experiences.
• Pipeline Management: Build and maintain robust end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, and validation.
• Generative AI Expertise: Fine-tune and deploy Generative AI models like CLIP, ViT, LoRA, LLaMA, DALL-E, or similar, for applications such as text generation, image synthesis, and multi-modal learning.
• Optimization and Tuning: Optimize and tune models for performance, scalability, and reliability to ensure they meet production standards.
• Collaboration: Work closely with data scientists, software engineers, and product teams to translate research prototypes into production-ready models, specifically in Generative AI and machine learning applications.
• MLOps and Deployment: Implement best practices for MLOps, including model versioning, testing, monitoring, and deployment in production environments using CI/CD pipelines.
• Continuous Learning: Stay up-to-date with the latest advancements in machine learning and Generative AI, and apply new techniques to improve our models and processes.
• Documentation and Support: Document processes and models, and provide technical guidance to other teams as needed.

Qualifications:

• Education: Bachelors or Master’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.

Skills and Experience:

• 5+ years of experience in machine learning, data science, or a related field.
• Strong proficiency in programming languages such as Python.
• Deep experience with machine learning frameworks like TensorFlow, PyTorch, and Keras, and libraries like scikit-learn.
• Proven track record in deploying Generative AI models (e.g., LLMs, DALL-E, ViT, CLIP, LoRA, LLaMA) in real-world applications.
• Strong expertise in NLP, image generation, and multi-modal models.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and tools like Docker, Kubernetes.
• Hands-on experience with MLOps practices, including model monitoring, retraining, and deploying in CI/CD pipelines.
• Strong understanding of algorithms, data structures, and software engineering principles.
• Experience with version control systems (e.g., Git) and collaborating in a team environment.

Preferred Qualifications:

• Experience with RESTful APIs and integration.
• Familiarity with big data technologies like Spark, Hadoop, or similar.
• Expertise in deep learning architectures such as transformers, convolutional neural networks (CNNs), and GANs.
• Knowledge of advanced MLOps tools like MLflow, Kubeflow, or Airflow.

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Why Join Us?

• Innovative Environment: Work with a forward-thinking team that values creativity and new ideas, particularly in the rapidly evolving field of machine learning.
• Professional Growth: Opportunities for continuous learning and career advancement, including access to the latest tools and technologies in machine learning.
• Collaborative Culture: Be part of a supportive and inclusive team that encourages collaboration and innovation across disciplines.
• Competitive Benefits: Enjoy a comprehensive benefits package, including health insurance, retirement plans, and paid time off, to support your well-being and work-life balance.

How to Apply:

• Alkye is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
• This job description incorporates the company’s focus on innovation, collaboration, and professional growth, tailored for the role of an ML Engineer.