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Machine Learning Engineer

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On-site

Job Type

Full Time

Job Description

We at TecMantras Solutions are seeking a skilled AI/ML Engineer to join our innovative team. In this

role, you will design, develop, and deploy machine learning models and systems that drive our

products and enhance user experiences. You will work closely with cross-functional teams to

implement cutting-edge AI solutions, including recommendation engines and large language models.


Required Technical Skill Set:

Data Science, Machine Learning, Data Analytics, Deep Learning,

Natural Language Processing, Business Intelligence, Computer Vision, Feature Engineering, Data

Mining, Data Processing, Data Visualization, SQL, Python, Transformers, Predictive Modelling,

Statistics, Text Analytics, MS Excel, Azure/ AWS, LLMs, MLOps, Generative AI, Deployment, Prompt

Engineering.


About the job

Role:

Required Technical Skill Set: Data Science, Machine Learning, Data Analytics, Deep Learning,

Natural Language Processing, Business Intelligence, Computer Vision, Feature Engineering, Data

Mining, Data Processing, Data Visualization, SQL, Python, Transformers, Predictive Modelling,

Statistics, Text Analytics, MS Excel, Azure/ AWS, LLMs, MLOps, Generative AI, Deployment, Prompt

Engineering.


Key Responsibilities:

  • Design and implement robust machine learning models and algorithms, focusing on recommendation systems.
  • Conduct data analysis to identify trends, insights, and opportunities for model improvement.
  • Collaborate with data scientists and software engineers to build and integrate end-to-end machine learning systems.
  • Optimize and fine-tune models for performance and scalability, ensuring seamless deployment.
  • Work with large datasets using SQL and Postgres to support model training and evaluation.
  • Implement and refine prompt engineering techniques for large language models (LLMs).
  • Stay current with advancements in AI/ML technologies, particularly in core ML algorithms like clustering and community detection.
  • Monitor model performance, conduct regular evaluations, and retrain models as needed.
  • Document processes, model performance metrics, and technical specifications.
  • Experienced in working with vector databases such as ChromaDB, Milvus, QdrantFAISS, Pinecone, Weaviate, etc for efficient similarity search and large-scale data retrieval.
  • Understanding of Large Language Models (LLM) And Other Generative AI (Genai) Models, Including Prompt Engineering, Model Evaluation, Stable Diffusion, Optimization And Deployment, LLMOps, LLM Training Framework’s/Deploying Tools like LangChain, LangGraph, CrewAI, AutoGen, etc.


Required Skills And Qualifications:

  • Bachelors or Master’s degree in Computer Science, Data Science, or a related field.
  • Strong expertise in Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Proven experience with SQL and Postgres for data manipulation and analysis.
  • Demonstrated experience building and deploying recommendation engines.
  • Solid understanding of core machine learning algorithms, including clustering and community detection.
  • Prior experience in building end-to-end machine learning systems.
  • Familiarity with prompt engineering and working with large language models (LLMs).
  • Experience working with near-real-time recommendation systems
  • Any graph databases hands-on experience like Neo4j, Neptune, etc
  • Experience in Flask or Fast API frameworks
  • Experience with SQL to write/modify/understand the existing queries and optimize DB connections
  • Experience with LLMs, using tools like OpenAI, Deepseek etc.
  • Presentation building skills
  • Experience with Agentic AI.
  • Familiarity with cloud platforms (AWS, Azure, Google Cloud) and MLOps tools.
  • Understanding of data structures, algorithms, and software engineering principles and also when to prototype.
  • Familiarity with version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes). Preferred Qualifications:
  • Hands-on experience with real-world AI applications, either through internships, research, or personal projects.
  • Knowledge of large-scale data handling and optimization techniques.
  • Experience with data preprocessing, feature engineering, and model evaluation techniques.
  • Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.


Why Join Us:

  • Flexible and friendly work environment
  • Opportunity to work on innovative projects
  • Continuous learning and growth
  • Leave enhancement policy and employee recognition


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