12 Model Tuning Jobs

As a skilled AI/ML Engineer, your primary responsibility will be to develop and train AI/ML models to enhance the functionalities of virtual humans, focusing on emotion detection, facial recognition, and speech synthesis. Your role will involve working on data preprocessing to ensure that datasets are clean, labeled accurately, and optimized for effective model training. Collaboration with senior engineers will be essential to implement and optimize deep learning models using frameworks such as TensorFlow, Keras, or PyTorch. Furthermore, you will play a key role in assisting in the deployment of AI models, guaranteeing their optimal performance in real-time applications. Your expertise will be required to conduct model evaluation and tuning, aiming to enhance accuracy, performance, and efficiency. Additionally, you will have the opportunity to contribute to research and innovation in AI applications for digital humans, exploring cutting-edge techniques in machine learning and AI. Join a company dedicated to creating hyper-realistic virtual influencers that elevate marketing returns for both brands and individuals. Be a part of an exciting journey with Kshan, India's first virtual influencer who can engage with people on various platforms like Instagram. Follow Kshan's lifestyle and witness the future of virtual interactions.,

You are a skilled and motivated AI Developer with over 3+ years of hands-on experience in building, deploying, and optimizing AI/ML models. Your expertise includes strong proficiency in Python, Scikit-learn, machine learning algorithms, and practical experience of Azure AI services, Azure AI foundry, Copilot Studio, and Dataverse are mandatory. You will be responsible for designing intelligent solutions using modern deep learning and neural network architectures, integrated into scalable cloud-based environments. Your key responsibilities will include utilizing Azure AI Foundry and Copilot Studio to build AI-driven solutions that can be embedded within enterprise workflows. You will design, develop, and implement AI/ML models using Python, Scikit-learn, and modern deep learning frameworks. Additionally, you will build and optimize predictive models using structured and unstructured data from data lakes and other enterprise sources. Collaborating with data engineers to process and transform data pipelines across Azure-based environments, you will develop and integrate applications with Microsoft Dataverse for intelligent business process automation. Applying best practices in data structures and algorithm design, you will ensure high performance and scalability of AI applications. Your role will involve training, testing, and deploying machine learning, deep learning, and neural network models in production environments. Furthermore, you will be responsible for ensuring model governance, performance monitoring, and continuous learning using Azure MLOps pipelines. Collaborating cross-functionally with data scientists, product teams, and cloud architects, you will drive AI innovation within the organization. As a qualified candidate, you hold a Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field. With 3+ years of hands-on experience in AI/ML development, you possess practical experience with Copilot Studio and Microsoft Dataverse integrations. Expertise in Microsoft Azure is essential, particularly with services such as Azure Machine Learning, Azure Data Lake, and Azure AI Foundry. Proficiency in Python and machine learning libraries like Scikit-learn, Pandas, and NumPy is required. A solid understanding of data structures, algorithms, and object-oriented programming is essential, along with experience in data lakes, data pipelines, and large-scale data processing. Your deep understanding of neural networks, deep learning frameworks (e.g., TensorFlow, PyTorch), and model tuning will be valuable in this role. Familiarity with MLOps practices and lifecycle management on cloud platforms is beneficial. Strong problem-solving abilities, communication skills, and team collaboration are important attributes for this position. Preferred qualifications include Azure AI or Data Engineering certification, experience in deploying AI-powered applications in enterprise or SaaS environments, knowledge of generative AI or large language models (LLMs), and exposure to REST APIs, CI/CD pipelines, and version control systems like Git.,

You will be joining our team as a Machine Learning / AI expert with 4-7 years of experience, dedicated to creating impactful GenAI solutions using Vertex AI on Google Cloud. If you are passionate about cutting-edge AI/LLM technologies and enjoy driving Proof of Concept (POC) delivery, we are excited to invite you to apply! Your responsibilities will include collaborating with both business and technical teams to define and implement GenAI/ML use cases as POCs. You will be responsible for building and deploying ML/GenAI models on Google Vertex AI, fine-tuning and evaluating LLMs for real-world applications, working closely with data engineers to design secure and scalable ML pipelines, as well as documenting and maintaining reproducible workflows. To succeed in this role, you must possess 4-7 years of hands-on experience in ML/AI project delivery. A strong foundation in machine learning, deep learning, and LLMs is essential. Proficiency with Vertex AI tools such as AutoML, Pipelines, Model Registry, and GenAI Studio is required. Strong Python skills with knowledge of TensorFlow, PyTorch, Hugging Face, and scikit-learn are also crucial. Experience in prompt engineering, model tuning, and evaluation, along with excellent collaboration and communication skills across cross-functional teams, are key attributes we are looking for. Additionally, familiarity with PaLM, Gemini, or other open-source LLMs, knowledge of LangChain, experience with GCP services like BigQuery, Cloud Functions, Cloud Storage, proficiency in CI/CD for ML, and understanding of Docker/Kubernetes are considered as bonus skills. A background in media/OTT/Web platforms and experience with large-scale media datasets would be advantageous for this role.,

As a Senior Data Scientist with 5+ years of experience, you will play a crucial role in our team based in Indore/Pune. Your responsibilities will involve designing and implementing models, extracting insights from data, and interpreting complex data structures to facilitate business decision-making. You should have a strong background in Machine Learning areas such as Natural Language Processing, Machine Vision, Time Series, etc. Your expertise should extend to Model Tuning, Model Validation, Supervised and Unsupervised Learning. Additionally, hands-on experience with model development, data preparation, and deployment of models for training and inference is essential. Proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis and exploration are key skills required for this role. You should be adept at developing code that enables reproducible data analysis. Familiarity with AWS services like Sagemaker, Lambda, Glue, Step Functions, and EC2 is expected. Knowledge of data science code development and deployment IDEs such as Databricks, Anaconda distribution, and similar tools is essential. You should also possess expertise in ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis. Your skills should include proficiency in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. Experience with end-to-end model deployment and production for at least 1 year is required. Familiarity with Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker is preferred. Basic knowledge of deep learning algorithms like MaskedCNN, YOLO, and visualization and analytics/reporting tools such as Power BI, Tableau, Alteryx would be advantageous for this role.,

You will be responsible for assisting in building and validating machine learning models as well as performing data cleaning, transformation, and feature engineering. Additionally, you will conduct exploratory data analysis using Python or R, support model tuning, performance tracking, and documentation. Collaboration with the team to apply AI/ML solutions to business use cases will be a key part of your role. You will also prepare clear reports and visualizations to present findings effectively. Applexus is a global technology leader that offers business consulting and SAP services to customers in the retail, fashion, and consumer products industries. Established in 2005, Applexus prioritizes customer satisfaction by developing technology solutions that facilitate business transformation. Headquartered in Seattle, Washington, Applexus operates across various centers in North America (Seattle & Canada), the United Kingdom, and India (Trivandrum & Chennai). The company is dedicated to making a positive impact by serving communities worldwide.,

As an AI/ML Manager at our Pune location, you will be responsible for leading the development of machine learning proof of concepts (PoCs) and demos using structured/tabular data for various use cases like forecasting, risk scoring, churn prediction, and optimization. Your role will involve collaborating with sales engineering teams to understand client requirements and presenting ML solutions during pre-sales calls and technical workshops. You will be expected to build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML, managing training, tuning, evaluation, and model packaging. Applying supervised, unsupervised, and semi-supervised techniques like XGBoost, CatBoost, k-Means, PCA, and time-series models will be a key part of your responsibilities. Working closely with data engineering teams, you will define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Packaging and documenting ML assets for scalability and transition into delivery teams post-demo will be essential. Staying updated with the latest best practices in ML explainability, model performance monitoring, and MLOps practices is also expected. Participation in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes are additional aspects of this role. To qualify for this position, you should have at least 8+ years of experience in developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries like XGBoost, CatBoost, LightGBM is required. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks is preferred. A solid understanding of feature engineering, model tuning, cross-validation, and error analysis is necessary. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques will be beneficial. You should be comfortable presenting models and insights to both technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection, will be an advantage. If you are interested in this opportunity, please apply or share your resume at kanika.garg@austere.co.in.,

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, you will be part of a team of bright individuals working with cutting-edge technologies. Our purpose is to bring about real positive changes in an increasingly virtual world, transcending generational gaps and future disruptions. We are currently looking to hire AI/ML Professionals for the position of AI Engineer with 24 years of experience on a full-time basis. As a highly skilled and motivated Data Scientist at YASH, you will be responsible for leveraging your advanced analytical and technical expertise to solve complex business problems and drive data-driven decisions. Your role will involve designing, developing, and deploying sophisticated machine learning models, performing in-depth data analyses, and collaborating with cross-functional teams to deliver actionable insights. Responsibilities: - Building and deploying ML models for classification, regression, and clustering tasks. - Applying foundational GenAI concepts such as embeddings, summarization, and RAG. - Utilizing APIs and tools like LangChain, vector databases (e.g., Pinecone, FAISS). - Preparing documentation and interpreting results effectively. Required Skills: - Strong hands-on experience in Python, Scikit-learn, and Pandas. - Knowledge of model evaluation, feature engineering, and model tuning. - Exposure to LangChain and vector databases. - Basic familiarity with FastAPI or Flask. At YASH, you will have the opportunity to create a career path that aligns with your aspirations while working in an inclusive team environment. We believe in leveraging career-oriented skilling models and utilizing technology for continuous learning, unlearning, and relearning at a rapid pace and scale. Our workplace culture at YASH is grounded in four principles: - Flexible work arrangements, free spirit, and emotional positivity. - Agile self-determination, trust, transparency, and open collaboration. - Providing all necessary support for the realization of business goals. - Offering stable employment with a great atmosphere and an ethical corporate culture.,

As a Senior Data Scientist with 5+ years of experience, you will be responsible for designing and implementing models, mining data for insights, and interpreting complex data structures to drive business decision-making. Your expertise in machine learning, including areas such as NLP, Machine vision, and Time series, will be essential in this role. You will be expected to have strong skills in Model Tuning, Model Validation, Supervised and Unsupervised Learning, and hands-on experience with model development, data preparation, training, and inference-ready deployment of models. Your proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis will help in developing code for reproducible analysis of data. Experience with AWS services like Sagemaker, Lambda, Glue, Step functions, and EC2 is necessary, along with knowledge of Databricks, Anaconda distribution, and similar data science code development and deployment IDEs. Your familiarity with ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis will be highly valued. You should have expertise in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. End-to-end model deployment and production experience of at least 1 year is required, along with a good understanding of Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker. Basic knowledge of deep learning algorithms such as MaskedCNN, YOLO, and familiarity with Visualization and analytics/Reporting Tools like Power BI, Tableau, and Alteryx will be considered advantageous for this role.,

Key Responsibilities: Build Scale AI ProductsDevelop and scale AI-driven B2C products with >1L MAU. Model ExpertiseWork withclosed models(OpenAI, Vertex AI)open-source LLMs(Llama, DeepSeek). Real-World AI ApplicationsFine-tune ground LLMs for domain-specific knowledge. Retrieval Function CallingImplement information retrieval and function-calling mechanisms. Evaluation FrameworksDesign long-term evaluation frameworks for AI performance improvements. What We re Looking For: 3-4 years of startup experiencewith managerial capability to build lead teams. Proven AI expertise, with a strong track record in applied AI LLMs. B2C Product SuccessBuilt and scaled AI-powered products with significant user adoption (>1L MAU). Hands-on experiencein AI frameworks, model tuning, and real-world LLM applications.

Good Programming Knowledge - Python, C++ Python Libraries -Numpy, Pandas DL framework - Pytorch, Keras Tensorflow, Scikit Learn AI Concepts - Strong fundamentals & working experience in Machine Learning (ML) Deep Learning (DL) Model Tuning, Optimization & Verification Transfer Learning Excellent understanding of lower level fundamentals of deep learning models such as layer details, attention, normalization, backpropagation, and optimizers. Tools Git Docker Collaboration tools (Ex. Confluence, Jira) Data analyst & Software Specialist Understand LG device data, pre-sales, post-sales data Derive insights Large Scale Data (Time series) Pre-processing & Analytics (w/ On-premise CPU&GPU server) Statistical Reasoning ML/DL (Fault Diagnosis, Energy), Parameter Tuning and Optimization Domain Specific Strong fundamentals & working experience in Exploratory Data Analysis (EDA) Remaining Useful Life Prediction Anomaly detection Regression problem solving Experience in Cloud Developer toolchains (AWS or MS Azure) Software development kit Data storage options, connections Compute/container deployment Debugging ETL process Mandatory Key Skills Python,C++,Numpy,Pandas,Machine Learning,Deep Learning,Tensorflow,Pytorch,Model Tuning,Docker,Git,ETL,AI- Vision*

Must Have Skills Good Programming Knowledge - Python, C++ Design: OOAD Python Libraries -Numpy, Pandas DL framework - Pytorch, Keras, Tensorflow, Scikit Learn AI Concepts - Strong fundamentals & working experience in Machine Learning (ML) Deep Learning (DL) Model Tuning, Optimization & Verification Transfer Learning Excellent understanding of lower level fundamentals of deep learning models such as layer details, attention, normalization, backpropagation, and optimizers. Good to have: Regression problem solving AI related certification - NLP / Vision / Audio / IOT Concepts of GPU based model training Open source NLP toolchain Hands on experience in NLP, NLU, NLG tasks Preferred candidate profile Total Exp - 2 to 5 Years Notice Period - Immediate Location -Bangalore Candidate should be ok to work from office.

Good Programming Knowledge - Python, C++ Python Libraries -Numpy, Pandas DL framework - Pytorch, Keras Tensorflow, Scikit Learn AI Concepts - Strong fundamentals & working experience in o Machine Learning (ML) o Deep Learning (DL) o Model Tuning, Optimization & Verification o Transfer Learning Excellent understanding of lower level fundamentals of deep learning models such as layer details, attention, normalization, backpropagation, and optimizers. Tools Git Docker Collaboration tools (Ex. Confluence, Jira) Data analyst & Software Specialist Understand LG device data, pre-sales, post-sales data Derive insights Large Scale Data (Time series) Pre-processing & Analytics (w/ On-premise CPU&GPU server) Statistical Reasoning ML/DL (Fault Diagnosis, Energy), Parameter Tuning and Optimization Domain Specific Strong fundamentals & working experience in Exploratory Data Analysis (EDA) Remaining Useful Life Prediction Anomaly detection Regression problem solving Experience in Cloud Developer toolchains (AWS or MS Azure) Software development kit Data storage options, connections Compute/container deployment Debugging ETL process Mandatory Key Skills Python,C++,Numpy,Pandas,Machine Learning,Deep Learning,Tensorflow,Pytorch,Model Tuning,Docker,Git,ETL,AI- Vision*