4+ Scikit-Learn Jobs in Chennai | Scikit-Learn Job openings in Chennai

Job Title : Senior Machine Learning Engineer

Experience : 8+ Years

Location : Chennai

Notice Period : Immediate Joiners Only

Work Mode : Hybrid

Job Summary :

We are seeking an experienced Machine Learning Engineer with a strong background in Python, ML algorithms, and data-driven development.

The ideal candidate should have hands-on experience with popular ML frameworks and tools, solid understanding of clustering and classification techniques, and be comfortable working in Unix-based environments with Agile teams.

Mandatory Skills :

• Programming Languages : Python
• Machine Learning : Strong experience with ML algorithms, models, and libraries such as Scikit-learn, TensorFlow, and PyTorch
• ML Concepts : Proficiency in supervised and unsupervised learning, including techniques such as K-Means, DBSCAN, and Fuzzy Clustering
• Operating Systems : RHEL or any Unix-based OS
• Databases : Oracle or any relational database
• Version Control : Git
• Development Methodologies : Agile

Desired Skills :

• Experience with issue tracking tools such as Azure DevOps or JIRA.
• Understanding of data science concepts.
• Familiarity with Big Data algorithms, models, and libraries.

Are you passionate about the power of data and excited to leverage cutting-edge AI/ML to drive business impact? At Poshmark, we tackle complex challenges in personalization, trust & safety, marketing optimization, product experience, and more.

Why Poshmark?

As a leader in Social Commerce, Poshmark offers an unparalleled opportunity to work with extensive multi-platform social and commerce data. With over 130 million users generating billions of daily events and petabytes of rapidly growing data, you’ll be at the forefront of data science innovation. If building impactful, data-driven AI solutions for millions excites you, this is your place.

What You’ll Do

• Drive end-to-end data science initiatives, from ideation to deployment, delivering measurable business impact through projects such as feed personalization, product recommendation systems, and attribute extraction using computer vision.
• Collaborate with cross-functional teams, including ML engineers, product managers, and business stakeholders, to design and deploy high-impact models.
• Develop scalable solutions for key areas like product, marketing, operations, and community functions.
• Own the entire ML Development lifecycle: data exploration, model development, deployment, and performance optimization.
• Apply best practices for managing and maintaining machine learning models in production environments.
• Explore and experiment with emerging AI trends, technologies, and methodologies to keep Poshmark at the cutting edge.

Your Experience & Skills

• Ideal Experience: 6-9 years of building scalable data science solutions in a big data environment. Experience with personalization algorithms, recommendation systems, or user behavior modeling is a big plus.
• Machine Learning Knowledge: Hands-on experience with key ML algorithms, including CNNs, Transformers, and Vision Transformers. Familiarity with Large Language Models (LLMs) and techniques like RAG or PEFT is a bonus.
• Technical Expertise: Proficiency in Python, SQL, and Spark (Scala or PySpark), with hands-on experience in deep learning frameworks like PyTorch or TensorFlow. Familiarity with ML engineering tools like Flask, Docker, and MLOps practices.
• Mathematical Foundations: Solid grasp of linear algebra, statistics, probability, calculus, and A/B testing concepts.
• Collaboration & Communication: Strong problem-solving skills and ability to communicate complex technical ideas to diverse audiences, including executives and engineers.

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.