3+ years of hands-on experience
in building, training, and deploying machine learning models in a professional, production-oriented setting.
Demonstrable experience with
database creation and advanced querying
(e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts.
Proven expertise in
data blending, transformation, and feature engineering
, adept at integrating and harmonizing both structured (e.g., relational databases, CSVs) and unstructured (e.g., text, logs, images) data.
Strong practical experience with
cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Dataflow) is highly desirable.
Proficiency in programming languages commonly used in data science (e.g.,
Python
is preferred, R).
Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction) and experience with advanced techniques like
Deep Learning, Natural Language Processing (NLP), or Computer Vision
.
Experience with machine learning libraries and frameworks (e.g.,
scikit-learn, TensorFlow, PyTorch
).
Familiarity with
MLOps tools and practices
, including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines.
Experience with containerization technologies like
Docker
and orchestration tools like
Kubernetes
for deploying ML models as REST APIs.
Proficiency with
version control systems (e.g., Git, GitHub/GitLab)
for collaborative development.

Interested candidates share cv to dikshith.nalapatla@motivitylabs.com

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