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Machine Learning Engineer
Machine Learning Engineer

Machine Learning Engineer at Marj Technologies · Noida · 3 - 10 years · ₹7L - ₹10L / yr · Raised funding · Posted 19 Aug 2022

Marj Technologies's logo

Machine Learning Engineer

Shyam Verma's profile picture
Posted by Shyam Verma
3 - 10 yrs
₹7L - ₹10L / yr
Noida
Skills
skill iconData Science
skill iconMachine Learning (ML)
Natural Language Processing (NLP)
Computer Vision
recommendation algorithm

Job Description

We are looking for a highly capable machine learning engineer to optimize our deep learning systems. You will be evaluating existing deep learning (DL) processes, do hyperparameter tuning, performing statistical analysis (logging and evaluating model’s performance) to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.

You will be working with technologies like AWS Sagemaker, TensorFlow JS, TensorFlow/ Keras/TensorBoard to create Deep Learning backends that powers our application.
To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in Deep Learning role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software. To do this job successfully, you need exceptional skills in DL and programming.


Responsibilities

  • Consulting with managers to determine and refine machine learning objectives.

  • Designing deep learning systems and self-running artificial intelligence (AI) software to

    automate predictive models.

  • Transforming data science prototypes and applying appropriate ML algorithms and

    tools.

  • Carry out data engineering subtasks such as defining data requirements, collecting,

    labeling, inspecting, cleaning, augmenting, and moving data.

  • Carry out modeling subtasks such as training deep learning models, defining

    evaluation metrics, searching hyperparameters, and reading research papers.

  • Carry out deployment subtasks such as converting prototyped code into production

    code, working in-depth with AWS services to set up cloud environment for training,

    improving response times and saving bandwidth.

  • Ensuring that algorithms generate robust and accurate results.

  • Running tests, performing analysis, and interpreting test results.

  • Documenting machine learning processes.

  • Keeping abreast of developments in machine learning.

    Requirements

  • Proven experience as a Machine Learning Engineer or similar role.

  • Should have indepth knowledge of AWS Sagemaker and related services (like S3).

  • Extensive knowledge of ML frameworks, libraries, algorithms, data structures, data

    modeling, software architecture, and math & statistics.

  • Ability to write robust code in Python & Javascript (TensorFlow JS).

  • Experience with Git and Github.

  • Superb analytical and problem-solving abilities.

  • Excellent troubleshooting skills.

  • Good project management skills.

  • Great communication and collaboration skills.

  • Excellent time management and organizational abilities.

  • Bachelor's degree in computer science, data science, mathematics, or a related field;

    Master’s degree is a plus.

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About Marj Technologies

Founded :
2018
Type :
Products & Services
Size :
0-20
Stage :
Raised funding

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● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

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● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

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Machine Learning & LLM Capability:

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 Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.

 Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.

 Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex.

 Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.

 Project Ownership & Execution

 Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.

 Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.

 Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.

 Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.

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 High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.

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Qualifications:

 Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.

 Proven expertise in Python, system design, and scalable AI/ML architecture.

 Deep knowledge of NLP, Computer Vision, and Deep Learning models.

 Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).

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We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.

 

 

 

Key Responsibilities

 

·      Design, develop, and deploy machine learning models for real-world business problems

·      Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring

·      Implement and manage MLOps pipelines for scalable and reproducible workflows

·      Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management

·      Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications

·      Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions

·      Optimize model performance and ensure production stability

·      Stay updated with the latest advancements in AI/ML and GenAI ecosystems

 

 

 

Required Skills & Qualifications

 

·      4+ years of experience in Data Science / Machine Learning

·      Strong programming skills in Python

·      Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)

·      Solid understanding of MLOps practices and tools

·      Experience with MLflow or similar model lifecycle tools 

·      Practical experience in Generative AI (GenAI), including working with LLMs

·      Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch

·      Strong understanding of data structures, algorithms, and statistics

·      Experience with cloud platforms (AWS/GCP/Azure) is a plus


Good to Have

 

·      Experience with LLM fine-tuning, prompt engineering, or RAG pipelines

·      Exposure to Docker, Kubernetes, and CI/CD pipelines

·      Knowledge of data engineering workflows 



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This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde


Key Objectives and Major Responsibilities:

• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team


Key Capabilities and Competencies:

Knowledge, Skills, Qualification and Experience

• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies. 

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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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