Associate Machine Learning Architect

Job Description

We seek an experienced Senior Machine Learning Architect (6+ years) with expertise in cloud (AWS, Azure and GCP)  to join our core tech team. The ideal candidate will have a deep understanding of machine learning algorithms and be responsible for designing, building, and deploying ML models in production. You will work closely with cross-functional teams, including data scientists, software engineers, and product managers, to understand requirements and deliver high-quality solutions. 

Key Responsibilities: 

With clients and stakeholders  

• Collaborate with stakeholders to understand requirements for data structure, availability, scalability & access, and transform business requirements to working real life applications with machine learning. 
• Develop a working understanding of the domain to effectively define problems and possible use cases. 
• Understand the data in customer experience domain and perform feature engineering and develop machine learning use cases. 
• Create prototypes of ML use cases and present to stakeholders. 

Machine learning development  

• Design and build machine learning models using appropriate ML Algorithms and Tools. 
• Establish and maintain data pipelines. 
• Deploy machine learning models in production and monitor their performance. 
• Collaborate with infrastructure and operations teams to architect and implement performance-tuning solutions for data storage and analytics. 

Organization and administration  

• Assist in data governance quality assurance for oversight, monitoring and reporting results. 
• Evaluate tools and techniques to support estimation of effort, costs, and bill of materials, and create common ground for the solution to be developed. 
• Mentor ML engineers and provide technical guidance and support. 
• Keep abreast of the latest advancements in machine learning technologies. 

Key Qualifications: 

Professional  

• Bachelor’s or master’s degree in computer science, mathematics, statistics or a related field. 
• At least 6 years of experience in machine learning, and a strong understanding of classical algorithms, including but not limited to regression, support vector machines, gradient-boosted decision trees, deep learning, etc. 

Relevant experience  

• Working experience with Machine Learning and Deep Learning use cases and algorithms. 
• Experience with ML Frameworks, Tools, and Environment: Scikit learn, TensorFlow, PyTorch, and PySpark. 
• Strong programming skills in Python and its programming environment – python IDE, Jupyter, Visual Studio Code/PyCharm, etc. 
• Experience with cloud computing, including AWS, Azure and GCP ML services 
• Experience building data pipelines, deploying machine learning models in production, and monitoring and maintaining their performance. 
• Experience with relational and non-relational databases, including SQL fluency. 
• Familiarity with data warehousing concepts – schemas, operational data stores, feature stores, DataMart. 
• Understanding of software development life-cycle process, and DevOps. 
• Good to have experience in developing, fine-tuning, and optimizing large language models, such as GPT-3, BERT, or similar. 

Soft skills  

• Excellent communication and collaboration skills. 
• Attention to detail, a true passion for problem-solving, and fastidious organisational tendencies. 
• Ability to work independently and in a team-oriented environment.