Data Scientist / ML Engineer

Cynosure Corporate Solutions; Chennai District; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Cynosure Corporate Solutions is seeking a skilled ML Engineer/Data Scientist to apply fundamentals of ML and statistics to real-world problems in a collaborative, global environment.

You will work with medium to large-scale datasets, perform EDA, and design ML solutions for CV, NLP, LLMs, and VLMs, leveraging GenAI and agentic AI. Strong MLOps, containerization, and cross-functional communication are essential.

Qualifications

• Hands-on experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch.
• Experience with NLP, embeddings, and transformer-based models.
• Expertise in vector search, similarity algorithms, and clustering.
• Strong Python programming with NumPy and Pandas.
• Proficient Git usage and collaborative coding practices.
• Familiar with Azure, Docker, and Kubernetes.
• Analytical, research-driven with hypothesis testing.
• Effective documentation and cross-functional teamwork.

Responsibilities

• Apply ML fundamentals to real-world problems.
• Work with medium to large-scale datasets.
• Conduct EDA and curate high-quality datasets.
• Design ML solutions for CV, NLP, LLMs, and VLMs.
• Formulate hypotheses, prototype models, validate KPIs.
• Leverage GenAI and Agentic AI in projects.
• Collaborate in international teams with clear docs.
• Apply MLOps best practices for reproducibility.
• Use Docker/containers for ML workflows.
• Align ML with business objectives.

Skills

Machine Learning Expertise

NLP & LLMs

Vector Search & Similarity

Python Programming

Version Control

Cloud & DevOps

Analytical Mindset

Documentation & Communication

Tools

Docker

Kubernetes

FAISS

Milvus

Pinecone

Hugging Face Transformers

Git

TensorFlow

PyTorch

Scikit-learn

NumPy

Pandas

Job description

Cynosure Corporate Solutions | Full time

Cynosure Corporate Solutions is a human capital services company. Our focus is to provide Executive Search, Recruitment, Training, Temporary Staffing services, Statutory Compliance's, and other HR aligned services. We understand the business goals of our clients and their need to align human resources to these goals. We are committed to provide high quality manpower in accordance to global standards and their requirements. Our candidates stand testimony to our professional competency.

We work with clients in IT/ITES, Manufacturing, Automobile, Health, Telecom, Media.

Job Description

Key Responsibilities

• Apply strong fundamentals and academic knowledge of Machine Learning algorithms and statistics to real-world problems.
  
• Work with medium to large-scale datasets, including time-series, anomaly detection, text, and image data.
  
• Conduct exploratory data analysis (EDA), curate high-quality datasets, and perform error analysis for ML and software algorithms.
  
• Design and implement ML solutions for Computer Vision, NLP, LLMs, and VLMs.
  
• Follow a methodical approach: formulate hypotheses, prototype models, and validate performance using measurable KPIs.
  
• Leverage GenAI and Agentic AI advancements in projects.
  
• Collaborate in international teams/projects, maintaining strong communication and documentation standards.
  
• Apply MLOps best practices, ensuring reproducibility, scalability, and deployment readiness.
  
• Use Docker and other containerization/orchestration tools for ML workflows.
  
• Align ML solutions with business objectives, ensuring strong business acumen in problem-solving.
  

Required Skills

• Machine Learning Expertise: Hands-on experience with frameworks such as Scikit-learn, TensorFlow, PyTorch.
  
• NLP & LLMs: Strong understanding of text embeddings, transformer-based models (e.g., BERT, RoBERTa, GPT, Hugging Face Transformers).
  
• Vector Search & Similarity Algorithms: Proficiency in FAISS, Milvus, Pinecone, and knowledge of cosine similarity, dot-product scoring, clustering methods.
  
• Programming: Strong Python skills with NumPy, Pandas, Scikit-learn, and ML/AI libraries.
  
• Version Control: Proficiency with Git and collaborative coding practices.
  
• Cloud & DevOps: Familiarity with Azure (preferred), Docker, and Kubernetes.
  
• Analytical Mindset: Curious, research-driven, with the ability to transition from hypothesis to validated ML solutions.
  
• Documentation & Communication: Ability to produce high-quality documentation and work effectively in cross-functional teams.