ML Engineer
2 days ago
I'm helping
Motivity Labs,
find a top candidate to join their team
full-time
for the role of
ML Engineer
.
You'll build and deploy production-ready machine learning models on cloud platforms.
Compensation:
Provide your expected compensation while applying
Location:
Magellanic-Cloud, Knowledge City Road, Silpa Gram Craft Village, Rai Durg, Telangana, India
Mission of Motivity Labs,:
"Our mission is to strengthen the critical success factors of every organization that leverages our IT Services. Due to this Motivity Labs aspires to innovate alongside our clients to ensure value is created at each step. We are highly dedicated to maximizing the happiness and success of every client that chooses Motivity Labs.
The world of technology is constantly evolving and undergoing complex transformations. Because of this, our experts at Motivity Labs go through extensive training and continuing education programs. Therefore we can always ensure they are knowledgeable about the most advanced solutions. In conclusion, our number one job is to constantly innovate and deliver value to transform the way you do business."
What makes you a strong candidate:
- You have +5 years experience in Deep learning.
- You are proficient in SQL, REST API, Docker, Databases, Data science.
- English - Fully fluent
Responsibilities and more:
5+ 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.
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