Machine Learning Engineer

3 months ago

Bengaluru, India Randstad Digital Full time

Experience : 4-7 Years

Location : Bangalore (WFO)

Looking for Immediate Joiners only.

Responsibilities :

- Build, Refine and Use ML Engineering platforms and components.

- ML Engineers with strong background in deploying and operationalizing ML models, Deep Learning Models (with focus on LLMs)

- Scaling machine learning algorithms to work on massive data sets and strict SLAs.

- Build and orchestrate model pipelines including feature engineering, inferencing and continuous model training.

- Implement ML Ops including model KPI measurements, tracking, model drift & model feedback loop.

- Collaborate with client facing teams to understand business context at a high level and contribute in technical requirement gathering.

- Implement basic features aligning with technical requirements.

- Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors.

- Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews.

- Write unit tests as well as higher level tests to handle expected edge cases and errors gracefully, as well as happy paths.

- Uses bug tracking, code review, version control and other tools to organize and deliver work.

- Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues and dependencies.

- Consistently contribute in researching & evaluating latest architecture patterns/technologies through rapid learning,

conducting proof-of-concepts and creating prototype solutions.

Qualifications :

- A master's or bachelor's degree in Compute Science or related field from a top university.


- 4+ years' hands-on experience in ML development.


- Good fundamentals of machine learning and deep learning


- Experienced in backend API design, vector DB.


- Strong programming expertise in Python, PySpark/Scala.


- Expertise in crafting ML Models for high performance and scalability.


- Experience in implementing feature engineering, inferencing pipelines, and real time model predictions.


- Experience in ML Ops to measure and track model performance, experience working with

MLFlow


- Experience with Spark or other distributed computing frameworks.


- Experience in ML platforms like Sage maker, Airflow, Kubeflow, Tensorflow/Kears/Pytorch, or

other platforms.


- Experience in deploying models to cloud services like AWS, Azure, GCP, Azure ML.


- Expertise in SQL, SQL DB's.


- Knowledgeable of core CS concepts such as common data structures and algorithms.



- Collaborate well with teams with different backgrounds / expertise / Skills :


- Understanding of DevOps, CI / CD, data security, experience in designing on cloud platform

- Experience in data engineering in Big Data systems


(ref:hirist.tech)

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