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Senior AI/ML Engineer

Senior AI/ML Engineer

Guide&Bridge

3 years

0 Lacs

pune maharashtra india

Posted:1 day ago| Platform:

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Skills Required

ai ml design learning data algorithms preprocess scalability training monitoring research numpy tensorflow pytorch statistics vision sql nosql aws sagemaker gcp vertex azure software engineering git docker reinforcement spark visualization tableau power matplotlib model

Work Mode

On-site

Job Type

Full Time

Job Description

Job Title: AI/ML Engineer

Experience Required: 3+ Years

About the Role

AI/ML Engineer

Key Responsibilities

Design, build, and deploy
machine learning and deep learning models
for real-world applications.
Collaborate with data engineers and scientists to collect, clean, and preprocess data.
Optimize models for performance, scalability, and accuracy.
Implement MLOps practices for continuous training, monitoring, and deployment.
Research and experiment with new algorithms, techniques, and tools in AI/ML.
Work with stakeholders to define use cases and integrate AI solutions into products.
Document processes, models, and workflows for knowledge sharing.

Required Skills & Qualifications

Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, or related field.
3–7 years of experience in AI/ML development.
Strong proficiency in
Python
and ML libraries (scikit-learn, NumPy, Pandas).
Hands-on experience with
deep learning frameworks
(TensorFlow, PyTorch, Keras).
Solid understanding of
machine learning algorithms, statistics, and data structures
.
Experience with
NLP, Computer Vision, or Recommendation Systems
.
Familiarity with
SQL/NoSQL databases
and working with large-scale datasets.
Exposure to
cloud platforms
(AWS Sagemaker, GCP Vertex AI, Azure ML).
Good knowledge of software engineering practices (Git, CI/CD, Docker, Kubernetes).

Good to Have

Experience with
reinforcement learning or generative AI models (LLMs, GANs, Transformers)
.
Familiarity with big data frameworks (Spark, Hadoop).
Knowledge of data visualization tools (Tableau, Power BI, matplotlib, seaborn).
Prior exposure to
MLOps pipelines and model monitoring tools
.

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