Sr. Machine Learning Engineer

What will you be doing?

• Design and develop advanced Machine Learning (ML) models to solve challenging problems related to natural language processing (NLP), recommendation systems, and predictive analytics.
• Collaborate with product and engineering teams to understand business needs and identify opportunities for the application of ML and AI technologies.
• Lead the exploration of new ML techniques and technologies to enhance the capabilities of our products and improve the user experience.
• Pioneer the exploration and adoption of new Generative AI techniques
• Mentor junior engineers and ML specialists, fostering a culture of innovation and continuous learning within the team.
• Ensure the quality and availability of data for model training and evaluation.
• Continuously evaluate and improve the performance and scalability of ML models in production environments.
• Stay abreast of developments in the field of ML and AI, and advocate for the adoption of industry best practices and emerging technologies.

What skills and experience do you need?

• 5+ years of experience in designing, implementing, and deploying ML models, with a strong portfolio of projects that demonstrate your expertise.
• Deep understanding of ML algorithms, data structures, and software engineering principles.
• Proficiency in programming languages such as Python and experience with ML frameworks like TensorFlow, PyTorch.
• Demonstrable experience driving impact by building production applications using ML models and learning based on production analytics and data.
• Practical experience with natural language processing (NLP) technologies, recommendation systems, predictive analytics, Generative AI.
• Strong experience with prompting techniques, RAG pipelines, evaluation mechanisms and fine-tuning SLMs, LLMs preferred.
• Strong problem-solving skills and the ability to work independently as well as in a team environment.
• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Bonus:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
• Experience with cloud computing platforms like AWS, Google Cloud Platform, or Azure, especially with services related to ML and data analytics.
• Familiarity with MLOps tools like Weights & Biases, MLFlow, Metaflow, Modal, etc.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes, particularly in the context of deploying and scaling ML models.
• Advanced knowledge in specialized areas of ML such as deep learning, reinforcement learning, or unsupervised learning techniques.Contributions to open-source ML projects or active participation in ML communities and conferences.
• Experience in developing and implementing ML solutions in the SaaS industry or for collaborative/team-based applications.
• Practical experience with big data technologies such as Hadoop, Spark, or Kafka for processing and analyzing large datasets.
• Proficiency in additional programming languages (e.g., JavaScript, R) or experience with front-end technologies (e.g., JavaScript, React, Angular) for end-to-end ML system development.
• Published research papers in top ML or AI conferences and journals.