Senior Machine Learning Engineer

Role & Responsibilities:

Developing high-level solution architectures and working with our offshore team of big-data engineers and decision science analysts to build, test and assess models that predict and optimize business outcomes based on client’s success criteria.
Develop sophisticated yet simple interpretations and communicate insights to clients that lead to quantifiable business impact.
Building deep relationships with clients by understanding their stated but more importantly, latent needs.
Working closely with the offshore delivery managers to ensure a seamless communication and delivery cadence. Researching and identifying sales opportunity, generating leads, target identification and classification
Serve as a mentor or guide for junior resources / freshers. 
Lead the technical discussion with the clients regarding updates / risks / blockers, etc. Fluent in communication

Skills expectation:

Must have:
Ability to think creatively and work well both as part of a team and as an individual contributor
Critical eye for the quality of data and a strong desire to get it right.
A pleasantly forceful personality and charismatic communication style.
Someone who will raise the average effectiveness of the team. In short, we are looking for a “Difference Maker”.
3+ years’ hands-on experience of Hands-on in model development, deployment, and operationalization of projects in statistical ML, NLP, etc
Python, with proficiency in class-based coding.
Strong understanding of coding standards and CI/CD practices.
Proficient in SQL for data analytics including querying, analyzing and processing large datasets.
ML development experience, particularly in statistical ML regression and classification models.
NLP expertise, including embedding techniques and transformers, clustering methods. 
Knowledge of statistical techniques for data analysis.
Understanding of MLOps basics, including model training, data/model monitoring, and retraining.
Strong theoretical understanding of Machine Learning concepts, as well as DeepLearning-based architectures, cloud-based web services architecture, design patterns, and frameworks
Comfortable with exploring new research and engineering/development best practices types
Hands-on experience working on and handling projects in the healthcare domain would be a desired skill
Experience in implementing Deep Learning solutions about, but not restricted to, reinforcement Learning, Natural Language Processing, and Auto ML. 
Exposure to the latest cutting-edge research. Ability to implement a research paper, as well as augment the current solution and communicate it to clients and team
Great analytical skills, with expertise in analytical toolkits such as Logistic Regression, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modeling, and predictive analysis.

Good to have:
Previous experience working in the healthcare domain.
GenAI skills, with a focus on prompt engineering and RAG concepts.
Basic hands-on experience working on projects catering to Natural Language Processing would be a good skill
Worked on Databricks for Model development. 
Hands-on experience with statistical tools and techniques.
Basics of Pyspark for data processing.
Experience with Agile/Scrum/DevOps software development methodologies.
Behavioural skills:

Effective communication with all the stakeholders involved
Communicate clearly about complex subjects and technical plans with technical and nontechnical audiences.
Ability to mentor and groom junior members of the team and provide them with guidance and a roadmap. 
Must also have the ability to interact with other members of the team (Juniors, Seniors, ATA, TA, BA, etc) to get their designs from concept to development