Senior Machine Learning Engineer(mlops)
1 week ago
Tredence is Data science, engineering, and analytics consulting company that partners with some of the leading global Retail, CPG, Industrial and Telecom companies.
We deliver business impact by enabling last mile adoption of insights by uniting our strengths in business analytics, data science and data engineering.
Headquartered in the San Francisco Bay Area, we partner with clients in US, Canada, and Europe.Bangalore is our largest Centre of Excellence with skilled analytics and technology teams serving our growing base of Fortune 500 clients.
JOB DESCRIPTION
As a Machine Learning Engineer, you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies.
As MLOps Engineer, you will ensure that deployed models are well maintained, performing as expected, and not having any adverse effects on the business.
You will collaborate with business partners and domain experts to design and develop innovative solutions with the models to achieve predefined outcomes.
THE IDEAL CANDIDATE WILL
Engage with clients to understand current and future business goals and translate business problems into high level solution approach
Work hands-on on building the model deployment and monitoring pipelines based on in-depth understanding of underlying data, data structures, and business problems to ensure deliverables meet client needs
Effectively communicate the approach and insights to a larger business audience
Collaborate with team members, peers and leadership at Tredence and client companies
ELIGIBILITY CRITERIA
BE/BTech/MTech (Specialization/courses in ML/DS)
3-7 years of hands-on experience building the end-to-end design, development, and deployment of predictive modelling solutions.
3+ years of experience in Python/R, SQL
3+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
2+ hands on work experience in Dev Ops
MLOPs skills like Feature Store, mlflow, model registry, microservices architecture, Flask, Docker, Kubernetes – Combination of these skills
Exposure on Azure cloud technologies like Databricks, Azure, Azure ML, Azure Monitor
Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
Knowledge of Deep Learning frameworks:
Keras, Tensorflow, Py Torch, etc
Experience with one or more Container-ecosystem (Docker, Kubernetes)
Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
Good understanding of OOP & Data Structures concepts
Proficient in Shell Scripting and automation tools
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