55 Gensim Jobs - Page 2

Job Responsibilities: Design, develop and implement solutions for a wide range of NLP use cases involving classification, extraction and search on unstructured text data Create and maintain state of the art scalable NLP solutions in Python/ Java/ Scala for multiple business problems. This involves: Choosing most appropriate NLP technique(s) based on business needs and available data Performing data exploration and innovative feature engineering Training and tuning a variety of NLP models / solutions which include regular expressions, traditional NLP models as well as SOTA transformer based models Augmenting models by integrating domain specific ontologies and/or external databases Reporting and Monitoring the solution outcome Work experience with document-oriented databases such as MongoDB Collaborate with ML engineering team to deploy NLP solutions in production - both on premise as well as cloud deployment Interact with clients and internal business teams to perform solution feasibility as well as design and develop solutions Open to working across different domains – Insurance, Healthcare and Financial Services etc. Required Skills: Experience (including graduate school) on training machine learning models, applying and developing text mining and NLP techniques Exposure to OCR and computer vision Experience in extracting content from documents is preferred Experience (including graduate school) with Natural Language Processing techniques is required Hands on experience with Natural Language Processing tools such as Stanford CORE-NLP, NLTK, spaCy, Gensim, Textblob etc. Experience/ Familiarity with document clustering in supervised un un-supervised scenarios Expertise in at least two of the state of the art techniques in NLP like BERT, GPT, XL Net etc. Applied experience of machine learning algorithms using Python Organized, self-motivated, disciplined and detail oriented Production level coding experience in Python is required Ability to read recent ML research papers and adapt those models to solve real-world problems Experience with any deep learning framework, including Tensorflow, Caffe, MxNet, Torch, Theano Experience with optimization on GPUs (a plus) Hands on experience with using cloud technologies on AWS/ Microsoft Azure is preferred

Dear Candidate, We are hiring a Computer Vision Engineer to develop AI-driven solutions for image recognition, object detection, and video analysis. The role requires expertise in deep learning, computer vision algorithms, and real-time processing techniques. Key Responsibilities: Develop and optimize computer vision models using OpenCV, TensorFlow, and PyTorch. Implement object detection, segmentation, and facial recognition algorithms. Process and analyze large-scale image and video datasets. Optimize deep learning models for real-time inference on edge devices. Collaborate with AI and software teams to integrate vision solutions into applications. Required Skills & Qualifications: Computer Vision Frameworks: OpenCV, DLIB, MediaPipe Deep Learning: TensorFlow, PyTorch, Keras Algorithms: CNNs, YOLO, Faster R-CNN, Mask R-CNN Programming: Python, C++, CUDA Edge AI: TensorRT, OpenVINO, NVIDIA Jetson Experience with autonomous systems, OCR, and SLAM is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies

Data Scientist (NLP) Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP) Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Qualifications: Bachelor's/Master's degree in Computer Science, Engineering, or a related technical field with minimum 3 years experience. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Practical hands-on fine-tuning/transfer learning/optimization of the Transformer architecture-based Deep Learning models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Deployment of the ML models on the Kubernetes clusters Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems. Interested candidates, please send their resumes to iqbal.kaur@birdeye.com Regards Iqbal kaur

Assistant Manager EXL/AM/1265152 Digital SolutionsNoida Posted On 26 May 2025 End Date 25 Jun 2025 Required Experience 2 - 4 Years Basic Section Number Of Positions 3 Band B1 Band Name Assistant Manager Cost Code G090637 Campus/Non Campus NON CAMPUS Employment Type Permanent Requisition Type Backfill Max CTC 600000.0000 - 1000000.0000 Complexity Level Not Applicable Work Type Hybrid – Working Partly From Home And Partly From Office Organisational Group EXL Digital Sub Group Digital Solutions Organization Digital Solutions LOB Digital Delivery Practice SBU Xtrakto.AI Country India City Noida Center Noida - Centre 59 Skills Skill DATA SCIENCE - AI COMPUTRE VISION NLP Minimum Qualification B.TECH/B.E MCA MSC Certification No data available Job Description Job Responsibilities: Design, develop and implement solutions for a wide range of NLP use cases involving classification, extraction and search on unstructured text data Create and maintain state of the art scalable NLP solutions in Python/ Java/ Scala for multiple business problems. This involves: Choosing most appropriate NLP technique(s) based on business needs and available data Performing data exploration and innovative feature engineering Training and tuning a variety of NLP models / solutions which include regular expressions, traditional NLP models as well as SOTA transformer based models Augmenting models by integrating domain specific ontologies and/or external databases Reporting and Monitoring the solution outcome Work experience with document-oriented databases such as MongoDB Collaborate with ML engineering team to deploy NLP solutions in production - both on premise as well as cloud deployment Interact with clients and internal business teams to perform solution feasibility as well as design and develop solutions Open to working across different domains – Insurance, Healthcare and Financial Services etc. Required Skills: Experience (including graduate school) on training machine learning models, applying and developing text mining and NLP techniques Exposure to OCR and computer vision Experience in extracting content from documents is preferred Experience (including graduate school) with Natural Language Processing techniques is required Hands on experience with Natural Language Processing tools such as Stanford CORE-NLP, NLTK, spaCy, Gensim, Textblob etc. Experience/ Familiarity with document clustering in supervised un un-supervised scenarios Expertise in at least two of the state of the art techniques in NLP like BERT, GPT, XL Net etc. Applied experience of machine learning algorithms using Python Organized, self-motivated, disciplined and detail oriented Production level coding experience in Python is required Ability to read recent ML research papers and adapt those models to solve real-world problems Experience with any deep learning framework, including Tensorflow, Caffe, MxNet, Torch, Theano Experience with optimization on GPUs (a plus) Hands on experience with using cloud technologies on AWS/ Microsoft Azure is preferred Workflow Workflow Type Digital Solution Center

Company Description Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 22,700 associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region. Job Description Education and Work Experience Requirements: 5 to 8 years of experience as Data Scientist or GenAI specialist· 2 to 3 years of experience in Generative AI solution development. Proven track record and experience with with GenAI technologies Open source LLMs like Llama, Gemma, Mixtral etco Closed source LLMs such as Open AI GPT, Azure Open AI, Claude, Gemini etco Prompt Engineering/Tuning, RAG, RAFT, LLM finetuning such as PEFT(LoRA, QLoRA ..) Understanding of SLMs such as Phi3, BERT and Transformer architectureo Vector databases like Pincone, Qdrant etc. Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model Expertise with the following scripting languages:o Python, R, Tensorflow, Keras, Pytorch OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs Good and experience of machine learning algorithms and ability to apply them in supervised and un-supervised NLP tasks. Knowledge of NLP algorithms that can handle various NLP tasks such as intent recognition, entity extraction, language modeling, text classification, question answering, text summarization, topic modeling and so on. Experience building and fine-tuning Language Models (LMs), such as BERT, ELMo, XLNet etc to solve bespoke NLP tasks. Tech savy and willing to work with open-Source Tools Should have independently handled a project technically and provided directions to the other Team Members. Able to lead the project independently. Experience in turning ideas into actionable designs. Able to persuade stakeholders and champion effective techniques through development. Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company. Good to have foundational knowledge on Cloud, API frameworks like Flask, Fast API, Swagger/Postman tools Prior experience working on Mobility or Healthcare domain will be a plus Mandatory Skills: · Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. Strong understanding of LLMs, and associated technologies like RAG, Agents, VectorDB and Guardrails Hand-on experience in GenAI frameworks like LlamaIndex, Langchain, Autogen, etc. · Experience in cloud services like Azure, GCP and AWS· Interact with our research team and with key partners in the market to build end-to-end AI/ML/NLP solutions: Conversational AI, document understanding and QnA. Mine and analyze data, applying statistical methods as necessary, pertaining to customers’ discovery, and viewing experiences to identify critical product insights. Proactively develop new metrics and studies to quantify the value of different aspects of product. Drive efforts to enable product and engineering leaders to share your knowledge and insights through clear and concise communication, education, and data visualization. Translate analytic insights into concrete, actionable recommendations for business or product improvement. Build and improve reusable tools & modelling pipelines and support knowledge sharing across several teams. Define and deploy best practices in Machine Learning & MLOps/LLMOps, mentor and teach colleagues. Partner closely with product and engineering leaders throughout the lifecycle of project Additional Information: A Master’s or PhD is preferred (Computer Science / Machine Learning/ Mechanical, etc) from tier 1 institutions. If Bachelors, Machine Learning or Computer Science specialization only Qualifications BE,BTech,MS, MTech or MCA Additional Information 7 to 10 years

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Natural Language Processing (NLP) Good to have skills : NA Minimum 5 Year(s) Of Experience Is Required Educational Qualification : BE Summary: As an AI / ML Engineer, you will develop applications and systems that utilize AI to improve performance and efficiency, including deep learning, neural networks, chatbots, and natural language processing. You will be at the forefront of cutting-edge technology, driving innovation and problem-solving in the field of AI and ML. Roles & Responsibilities: - Expected to be an SME, collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Provide solutions to problems for their immediate team and across multiple teams. - Lead research and development efforts in AI and ML technologies. - Implement and optimize machine learning models for various applications. - Conduct data analysis and interpretation to drive business insights. - Stay updated on the latest trends and advancements in AI and ML. Professional & Technical Skills: - Must To Have Skills: Proficiency in Natural Language Processing (NLP). - Strong understanding of deep learning algorithms and neural networks. - Experience in developing chatbots and conversational AI. - Knowledge of text mining and sentiment analysis techniques. - Hands-on experience with NLP libraries such as NLTK, SpaCy, or Gensim. Additional Information: - The candidate should have a minimum of 5 years of experience in Natural Language Processing (NLP). - This position is based at our Kolkata office. - A BE degree is required.

Job Responsibilities Design, develop and implement solutions for a wide range of NLP use cases involving classification, extraction and search on unstructured text data Create and maintain state of the art scalable NLP solutions in Python/ Java/ Scala for multiple business problems. This involves: Choosing most appropriate NLP technique(s) based on business needs and available data Performing data exploration and innovative feature engineering Training and tuning a variety of NLP models / solutions which include regular expressions, traditional NLP models as well as SOTA transformer based models Augmenting models by integrating domain specific ontologies and/or external databases Reporting and Monitoring the solution outcome Work experience with document-oriented databases such as MongoDB Collaborate with ML engineering team to deploy NLP solutions in production - both on premise as well as cloud deployment Interact with clients and internal business teams to perform solution feasibility as well as design and develop solutions Open to working across different domains – Insurance, Healthcare and Financial Services etc. Required Skills Experience (including graduate school) on training machine learning models, applying and developing text mining and NLP techniques Exposure to OCR and computer vision Experience in extracting content from documents is preferred Experience (including graduate school) with Natural Language Processing techniques is required Hands on experience with Natural Language Processing tools such as Stanford CORE-NLP, NLTK, spaCy, Gensim, Textblob etc. Experience/ Familiarity with document clustering in supervised un un-supervised scenarios Expertise in at least two of the state of the art techniques in NLP like BERT, GPT, XL Net etc. Applied experience of machine learning algorithms using Python Organized, self-motivated, disciplined and detail oriented Production level coding experience in Python is required Ability to read recent ML research papers and adapt those models to solve real-world problems Experience with any deep learning framework, including Tensorflow, Caffe, MxNet, Torch, Theano Experience with optimization on GPUs (a plus) Hands on experience with using cloud technologies on AWS/ Microsoft Azure is preferred

Education and Work Experience Requirements: · 5 to 8 years of experience as Data Science Architect · 2 to 3 years of experience in Generative AI solution development · Proven track record and experience with with GenAI technologies o Open source LLMs like Llama, Gemma, Mixtral etc o Closed source LLMs such as Open AI GPT, Azure Open AI, Claude, Gemini etc o Prompt Engineering/Tuning, RAG, RAFT, LLM finetuning such as PEFT(LoRA, QLoRA ..) o Understanding of SLMs such as Phi3,QWEN, BERT and Transformer architecture o Vector databases like Pinecone, Qdrant etc. · Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model · Expertise with the following scripting languages: o Python, R, Tensorflow, Keras, Pytorch o OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs · Design and implement end-to-end Generative AI solutions, ensuring seamless integration with enterprise applications and workflows. · Lead technical evaluations and POCs (Proof of Concepts) to assess new AI models, frameworks, and vector databases for RAG solutions. · Develop scalable indexing and retrieval strategies to optimize search and generation performance in large-scale AI systems. · Implement hybrid search techniques, including dense and sparse retrieval, for enhanced information retrieval accuracy. · Define and enforce architectural standards, coding best practices, and performance benchmarks for RAG-based applications. · Collaborate with business leaders to identify AI-driven opportunities and develop strategic roadmaps for AI product evolution. · Drive the adoption of domain-specific AI solutions by tailoring RAG architectures to industry-specific requirements. · Establish feedback loops and model monitoring mechanisms to ensure continuous improvement of AI-generated outputs. · Utilize MLOps best practices to automate model deployment, monitoring, and retraining pipelines for Generative AI solutions. · Optimize knowledge graphs and vector embeddings to enhance contextual awareness in Graph RAG implementations. · Develop strategies for handling long-context retrieval and efficient chunking mechanisms for better AI response quality. · Leverage fine-tuning and reinforcement learning with human feedback (RLHF) to improve generative AI model performance. · Explore and integrate federated learning techniques to enable privacy-preserving AI model training and inference. · Conduct AI ethics assessments and bias mitigation strategies to ensure responsible AI development and deployment. · Engage with open-source AI communities and contribute to research publications or technical blogs on RAG advancements. · Participate in technical panels, conferences, and industry events to showcase AI expertise and thought leadership. · Support sales and pre-sales teams by providing technical guidance, solution demonstrations, and AI-driven business value assessments. · Establish AI Centers of Excellence (CoE) within the organization to drive innovation, knowledge sharing, and AI capability building. · Ensure compliance with enterprise security policies, data governance regulations, and responsible AI guidelines. · Develop multi-modal AI capabilities that integrate NLP, Computer Vision, and Speech Recognition for advanced generative applications. · Prior experience working on Mobility, Manufacturing or Healthcare domain will be a plus. Mandatory Skills: · Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. · Strong understanding of LLMs, and asso Educational qualification: BE/BTech or MCA Experience : 10-15 years

Education and Work Experience Requirements: · 5 to 8 years of experience as Data Scientist · 2 to 3 years of experience in Generative AI solution development · Strong understanding of AI agent collaboration, negotiation, and autonomous decision-making. · Experience in developing and deploying AI agents that operate independently or collaboratively in complex environments. · Deep knowledge of agentic AI principles, including self-improving, self-organizing, and goal-driven agents. · Proficiency in multi-agent frameworks such as AutoGen, LangGraph, LangChain, and CrewAI for orchestrating AI workflows. · Hands-on experience integrating LLMs (GPT, LLaMA, Mistral, etc.) with agentic frameworks to enhance automation and reasoning. · Expertise in hierarchical agent frameworks, distributed agent coordination, and decentralized AI governance. · Strong grasp of memory architectures, tool use, and action planning within AI agents. · Autonomy Score: Measures the degree of independence in decision-making. · Collaboration Efficiency: Evaluates the ability of agents to work together and share information. · Task Completion Rate: Tracks the percentage of tasks successfully executed by agents. · Response Time: Measures the latency in agent decision-making and execution. · Adaptability Index: Assesses how well agents adjust to dynamic changes in the environment. · Resource Utilization Efficiency: Evaluates computational and memory usage for optimization. · Explainability & Interpretability Score: Ensures transparency in agent reasoning and outputs. · Error Rate & Recovery Time: Tracks failures and the system’s ability to self-correct. · Knowledge Retention & Utilization: Measures how effectively agents recall and apply information. · Hands-on experience with LLMs such as GPT, BERT, LLaMA, Mistral, Claude, Gemini, etc. · Proven expertise in both open-source (LLaMA, Gemma, Mixtral) and closed-source (OpenAI GPT, Azure OpenAI, Claude, Gemini) LLMs. · Advanced skills in prompt engineering, tuning, retrieval-augmented generation (RAG), reinforcement learning (RAFT), and LLM fine-tuning (PEFT, LoRA, QLoRA). · Strong understanding of small language models (SLMs) like Phi-3 and BERT, along with Transformer architectures. · Experience working with text-to-image models such as Stable Diffusion, DALL·E, and Midjourney. · Proficiency in vector databases such as Pinecone, Qdrant for knowledge retrieval in agentic AI systems. · Deep understanding of Human-Machine Interaction (HMI) frameworks within cloud and on-prem environments. · Strong grasp of deep learning architectures, including CNNs, RNNs, Transformers, GANs, and VAEs. · Expertise in Python, R, TensorFlow, Keras, and PyTorch. · Hands-on experience with NLP tools and libraries: OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Knowledge Graphs, and LLM-based applications. · Proficiency in advanced statistical methods and transformer-based text processing. · Experience in reinforcement learning and planning techniques for autonomous agent behavior. Mandatory Skills: · Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. · Strong understanding of LLMs, and associated technologies like RAG, Agents, VectorDB and Guardrails · Hand-on experience in GenAI frameworks like LlamaIndex, Langchain, Autogen, etc. · Experience in cloud services like Azure, GCP and AWS · Multi-agent frameworks: AutoGen, LangGraph, LangChain, CrewAI · Large Language Models (LLMs): GPT, Educational qualification: BE,BTECH or PHD

Dear Candidate, We are seeking a highly skilled and motivated Software Engineer with expertise in Azure AI , Cognitive Services, Machine Learning , and IoT. The ideal candidate will design, develop, and deploy intelligent applications leveraging Azure cloud technologies, AI-driven solutions, and IoT infrastructure to drive business innovation and efficiency. Responsibilities: Develop and implement AI-driven applications using Azure AI and Cognitive Services . Design and deploy machine learning models to enhance automation and decision-making processes. Integrate IoT solutions with cloud platforms to enable real-time data processing and analytics. Collaborate with cross-functional teams to architect scalable, secure, and high-performance solutions. Optimize and fine-tune AI models for accuracy, performance, and cost-effectiveness. Ensure best practices in cloud security, data governance, and compliance. Monitor, maintain, and troubleshoot AI and IoT solutions in production environments. Stay updated with the latest advancements in AI, ML, and IoT technologies to drive innovation. Required Skills and Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or a related field. Strong experience with Azure AI, Cognitive Services, and Machine Learning. Proficiency in IoT architecture, data ingestion, and processing using Azure IoT Hub , Edge , or related services. Expertise in deploying and managing machine learning models in cloud environments. Strong understanding of RESTful APIs, microservices, and cloud-native application development. Experience with DevOps practices, CI/CD pipelines, and containerization (Docker, Kubernetes). Knowledge of cloud security principles and best practices. Excellent problem-solving skills and the ability to work in an agile development environment. Preferred Qualifications: Certifications in Microsoft Azure AI, IoT, or related cloud technologies. Experience with Natural Language Processing (NLP) and Computer Vision. Familiarity with big data processing and analytics tools such as Azure Data. Prior experience in deploying edge computing solutions. Soft Skills: Problem-Solving: Ability to analyze complex problems and develop effective solutions. Communication Skills: Strong verbal and written communication skills to effectively collaborate with cross-functional teams. Analytical Thinking: Ability to think critically and analytically to solve technical challenges. Time Management: Capable of managing multiple tasks and deadlines in a fast-paced environment. Adaptability: Ability to quickly learn and adapt to new technologies and methodologies. Interview Mode : F2F for who are residing in Hyderabad / Zoom for other states Location : 43/A, MLA Colony,Road no 12, Banjara Hills, 500034 Time : 2 - 4pm

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters. The Position As a Data Scientist you will join the data science cluster in the Roche Informatics Data and Analytics Chapter (DnA). You will be part of one or several multi-disciplinary agile teams where you’ll actively shape the future of healthcare by using data science methods and principles to generate deeper insights from a great variety of data sources. To achieve this, you will proactively identify needs, design and implement analytical solutions, provide advice and consulting support to our key stakeholders and show impact by executing proof-of-value initiatives, or contributing to existing products. As a Data Scientist you will: Apply your expertise in NLP/LLM to develop and refine models that address Roche business needs. Involved in building and fine-tuning models and optimising their performance to provide valuable insights and solutions to business stakeholders Support prioritisation efforts, understand feasibility and business impact, take smart risks to make informed decisions in a fast-paced, evolving environment to deliver patient benefits faster Collaborate within global agile teams in the Roche Informatics business and foundational domains to develop products that provide the highest value to both Roche Pharma and Diagnostics business stakeholders. Provide methodical and implementation guidance as well as hands-on support around analytical LLM/NLP use cases. Evaluate the pros & cons of different NLP approaches and Generative AI platforms with comprehensive quantitative and qualitative analysis Communicate findings and market the value of use cases to key stakeholders Contribute to positioning data science as a key competency within the enterprise Continuously look for opportunities to broaden knowledge, capabilities and skill set to enable talent to flow into different specialties Be a role model for knowledge sharing within the DnA chapter. Act as a coach, mentor, or buddy to help colleagues grow and develop Qualifications M.Sc. or PhD in Computer Science, Physics, Statistics, Mathematics or equivalent degree and experience with machine learning/data mining/artificial intelligence. Experience of working as a hands-on data scientist in pharmaceutical industry is preferred Hands-on experience with Python programming and common NLP libraries (e.g., transformers, gensim, spaCy, etc.) Familiarity with essential frameworks (e.g. PyTorch) and infrastructure components (Docker, GPU) for training, fine-tuning and evaluating NLP tasks Experience in using both open source (e.g. HuggingFace) and closed source LLM models with different deep learning architectures Experience implementing RAG, working with knowledge databases and using LLM through APIs Good knowledge of effective training and optimising language models to fit for internal infrastructure and ensure seamless integration Familiarity with best practices for code generation, code documentation, data security, and compliance in cloud-based data science workflows Proven experience to add value and insight by providing advanced analytical solutions Data storytelling skills and using visualisation tools to communicate data and results with a non-technical audience International, goal oriented mindset with can do attitude Fluency in written and spoken English Who we are A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact. Let’s build a healthier future, together. Roche is an Equal Opportunity Employer. Show more Show less

Job Description Lead development of robust short / mid / long term industry and segment forecasts for specific regions around the world Conduct analysis of various factors that influence vehicle sales as well as Powertrain adoption (industry, macroeconomic, consume behavior, demographics, competitive cycle plan, regulatory trends etc.) Develop insightful reports and dashboards on various KPIs impacting vehicle sales and Powertrain growth using new age tools Develop new and/or enhance existing analytical tools and processes to improve volume-forecasting Support Business and Sales Planning Analytics activities and interactions with business customers in region Responsibilities Segmentation forecasts Segmentation forecasting models for key markets Short / mid-term forecasts Comprehensive segmentation analysis for key markets identifying drivers and trends Development/Maintenance of Sales Dashboards Qualifications 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 5+ years automotive experience in Marketing, Finance, Planning, Product Development and/or Sales Experience with statistical forecasting and / or developing statistical / Mathematical / AI models as well as hands on experience working on AI tools and cloud technologies Demonstrated ability to interface with personnel in diverse markets and/or functions as well as effectively and succinctly present analysis and recommendations to a diverse audience Show more Show less

The Global Data Insights and Analytics (GDI&A) department at Ford Motors Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization.The candidate should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Master's degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. Proficient in querying and analyzing large datasets using BigQuery on GCP. Strong Python skills for data wrangling and automation. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or QlikSense. 1+ years' experience in SQL programming language and relational databases. Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making by FCSD business team Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are seeking a talented and experienced AI/NLP Engineer to join our dynamic team. The ideal candidate will have a strong background in Artificial Intelligence (AI) , Natural Language Processing (NLP) and Machine Learning (ML) , with proven expertise in fine-tuning, deploying, and optimizing state-of-the-art NLP models. This role demands a hands-on approach to designing, developing, and integrating NLP solutions tailored to solve complex business challenges. If you are passionate about cutting-edge AI, have a knack for deploying scalable models in production environments, and enjoy collaborating with cross-functional teams, we’d love to hear from you! Key Responsibilities Model Development and Fine-tuning: Customize, fine-tune, and optimize open-source NLP models (e.g., LSTM/RNN based, Transformer-based, Conformer-based, and VITS architecture) using transfer learning. Develop and train models from scratch when needed to address specific business challenges. Generative AI & Prompt Engineering: Design effective prompts for generative AI tasks to meet diverse user and business requirements. Build similarity models (e.g., symmetric/asymmetric - gte, bge, Mini-LM) using BERT, XLNET, and cross-encoders for LLM-based Retrieval-Augmented Generation (RAG) use cases. Model Deployment & Optimization: Deploy models at scale using Docker, Kubernetes, and cloud platforms like AWS. Optimize models for performance using techniques such as vLLM (Paged Attention), quantization, and adapter-based fine-tuning - LoRA, QLoRA. Performance Monitoring and Enhancement: Continuously evaluate and enhance model performance to ensure accuracy, scalability, and minimal latency. Build pipelines for data preprocessing, model serving, and monitoring using tools like Airflow and AWS Batch. Collaboration: Work closely with data scientists, software engineers, and product teams to integrate NLP models seamlessly into business applications. Required Skills NLP & Machine Learning: 3+ years of experience in NLP, with expertise in fine-tuning, transfer learning, and developing custom models. Hands-on experience in ASR, TTS, or custom language model architectures (e.g., Auto-regressive transformers, RWKV). Generative AI & Prompt Engineering: Proficiency in designing and crafting prompts for generative AI models aligned with business use cases. Programming Skills: Strong proficiency in Python, with experience in implementing NLP models and building pipelines. Model Deployment: Hands-on experience with Docker, Kubernetes, and cloud-based deployment on platforms such as AWS. Deep Learning Frameworks: Proficiency with TensorFlow, PyTorch, and libraries like Hugging Face Transformers, NLTK, SpaCy, and Gensim. Bonus Skills MLOps & Cloud Services: Experience with AWS (Lambda, Step Functions, Batch), GCP, Azure, or Nemo for model deployment and pipeline management. Large-Scale Deployments: Expertise in scaling AI models and managing SLAs for real-world applications. Preferred Qualifications Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Proven track record of working with large datasets and creating robust pipelines for data ingestion and preprocessing. Strong understanding of neural networks and advanced deep learning architectures for NLP. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 – Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are seeking a talented and experienced AI/NLP Engineer to join our dynamic team. The ideal candidate will have a strong background in Artificial Intelligence (AI) , Natural Language Processing (NLP) and Machine Learning (ML) , with proven expertise in fine-tuning, deploying, and optimizing state-of-the-art NLP models. This role demands a hands-on approach to designing, developing, and integrating NLP solutions tailored to solve complex business challenges. If you are passionate about cutting-edge AI, have a knack for deploying scalable models in production environments, and enjoy collaborating with cross-functional teams, we’d love to hear from you! Key Responsibilities Model Development and Fine-tuning: Customize, fine-tune, and optimize open-source NLP models (e.g., Transformer-based, Conformer-based, and VITS architecture) using transfer learning. Develop and train models from scratch when needed to address specific business challenges. Generative AI & Prompt Engineering: Design effective prompts for generative AI tasks to meet diverse user and business requirements. Build similarity models (e.g., symmetric/asymmetric) using BERT, XLNET, and cross-encoders for LLM-based Retrieval-Augmented Generation (RAG) use cases. Model Deployment & Optimization: Deploy models at scale using Docker, Kubernetes, and cloud platforms like AWS. Optimize models for performance using techniques such as vLLM (Paged Attention), quantization, and adapter-based fine-tuning - LoRA, QLoRA. Performance Monitoring and Enhancement: Continuously evaluate and enhance model performance to ensure accuracy, scalability, and minimal latency. Build pipelines for data preprocessing, model serving, and monitoring using tools like Airflow and AWS Batch. Collaboration: Work closely with data scientists, software engineers, and product teams to integrate NLP models seamlessly into business applications. Required Skills NLP & Machine Learning: 6+ years of experience in NLP, with expertise in fine-tuning, transfer learning, and developing custom models. Hands-on experience in ASR, TTS, or custom language model architectures (e.g., Auto-regressive transformers, RWKV). Generative AI & Prompt Engineering: Proficiency in designing and crafting prompts for generative AI models aligned with business use cases. Programming Skills: Strong proficiency in Python, with experience in implementing NLP models and building pipelines. Model Deployment: Hands-on experience with Docker, Kubernetes, and cloud-based deployment on platforms such as AWS. Deep Learning Frameworks: Proficiency with TensorFlow, PyTorch, and libraries like Hugging Face Transformers, NLTK, SpaCy, and Gensim. Bonus Skills MLOps & Cloud Services: Experience with AWS (Lambda, Step Functions, Batch), GCP, Azure, or Nemo for model deployment and pipeline management. Large-Scale Deployments: Expertise in scaling AI models and managing SLAs for real-world applications. Preferred Qualifications Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Proven track record of working with large datasets and creating robust pipelines for data ingestion and preprocessing. Strong understanding of neural networks and advanced deep learning architectures for NLP. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less

Job Description The Global Data Insights and Analytics (GDI&A) department at Ford Motors Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization.The candidate should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Responsibilities Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making by FCSD business team Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Qualifications Master's degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. Proficient in querying and analyzing large datasets using BigQuery on GCP. Strong Python skills for data wrangling and automation. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or QlikSense. 1+ years' experience in SQL programming language and relational databases. Show more Show less

Job Type Full-time Description Why Birdeye? Birdeye is the highest-rated reputation, social media, and customer experience platform for local businesses and brands. Over 150,000 businesses use Birdeye’s AI-powered platform to effortlessly manage online reputation, connect with prospects through social media and digital channels, and gain customer experience insights to grow sales and thrive. At Birdeye, innovation isn't just a goal – it's our driving force. Our commitment to pushing boundaries and redefining industry standards has earned us accolades as one of the foremost providers of AI, Reputation Management, Social Media, and Customer Experience software by G2. Founded in 2012 and headquartered in Palo Alto, Birdeye is led by a team of industry experts and innovators from Google, Amazon, Salesforce, and Yahoo. Birdeye is backed by the who’s who of Silicon Valley - Salesforce founder Marc Benioff, Yahoo co-founder Jerry Yang, Trinity Ventures, World Innovation Lab, and Accel-KKR. Role Description: This is a full-time remote role for a Data Scientist at Bideye. Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP) Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Requirements Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 1-2 years' experience. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems. Why You’ll Join Us At Birdeye, we are relentless innovators driven by a singular goal: to lead our category with unparalleled excellence. We don't just set goals – we surpass them. We're a team of doers who roll up our sleeves and get the job done, delivering on our promises with unwavering dedication. Working here means embracing a culture of action and accountability, where every person is empowered to make an impact. We don't just talk about making a difference – we make it happen. Show more Show less

Main Responsibilities Participating in the design and development of end-to-end data science analytics solutions using associated technologies Independent development of the problem solution steps and coding functionalities and its implementation by analysis of input and desired output Perform data preprocessing, harmonization, and feature engineering to prepare modeling datasets. Job Requirement Bachelor’s or Master’s degree in Computer Science, Data science, Data Analytics or a similar fields 2-4 years of working experience Advance knowledge in Python programming and experiences in data science using Python (familiar with the libraries Pandas, Scikit-learn, Streamlit, SpaCy, Gensim, NLTK, re, Plotly, Matplotlib, huggingface, transformer, openai, Langchain) Professional experience in the development of web applications such as WebApps and REST APIs with JavaScript frameoworks and with Python Experience with PowerApps and PowerAutomate Experience with data visualization techniques such as PowerBI etc. Experience in Machine Learning especially in the field of supervised machine learning and classification (create, train, apply classifier and evaluate results) Experience in regular expressions and natural language processing creating preprocessing pipelines) Familiar with and comfortable using the latest technological tools, including ChatGPT Working experience with LLMs (incorporate LLMs in WebApps to solve business tasks) and creating prompts for various tasks utilizing Langchain Primary location BASF Innovation campus at Turbhe, Navi Mumbai Job Information technology/Service Show more Show less

As an expectation a fitting candidate must have/be: Ability to analyze business problem and cut through the data challenges. Ability to churn the raw corpus and develop a data/ML model to provide business analytics (not just EDA), machine learning based document processing and information retrieval Quick to develop the POCs and transform it to high scale production ready code. Experience in extracting data through complex unstructured documents using NLP based technologies. Good to have : Document analysis using Image processing/computer vision and geometric deep learning Technology Stack: Python as a primary programming language. Conceptual understanding of classic ML/DL Algorithms like Regression, Support Vectors, Decision tree, Clustering, Random Forest, CART, Ensemble, Neural Networks, CNN, RNN, LSTM etc. Programming: Must Have: Must be hands-on with data structures using List, tuple, dictionary, collections, iterators, Pandas, NumPy and Object-oriented programming Good to have: Design patterns/System design, cython ML libraries: Must Have: Scikit-learn, XGBoost, imblearn, SciPy, Gensim Good to have: matplotlib/plotly, Lime/sharp Data extraction and handling: Must Have: DASK/Modin, beautifulsoup/scrappy, Multiprocessing Good to have: Data Augmentation, Pyspark, Accelerate NLP/Text analytics: Must Have: Bag of words, text ranking algorithm, Word2vec, language model, entity recognition, CRF/HMM, topic modelling, Sequence to Sequence Good to have: Machine comprehension, translation, elastic search Deep learning: Must Have: TensorFlow/PyTorch, Neural nets, Sequential models, CNN, LSTM/GRU/RNN, Attention, Transformers, Residual Networks Good to have: Knowledge of optimization, Distributed training/computing, Language models Software peripherals: Must Have: REST services, SQL/NoSQL, UNIX, Code versioning Good to have: Docker containers, data versioning Research: Must Have: Well verse with latest trends in ML and DL area. Zeal to research and implement cutting areas in AI segment to solve complex problems Good to have: Contributed to research papers/patents and it is published on internet in ML and DL Morningstar is an equal opportunity employer. Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We’ve found that we’re at our best when we’re purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues. I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity Show more Show less

Lead Data Scientist Title: Lead Data Scientist Role Description: This is a full-time remote role for a Lead Data Scientist at Birdeye. Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP), MLOps Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Lead and mentor a team of data scientists, providing guidance on best practices and technical expertise. Collaborate with cross-functional teams to define data-driven strategies and integrate data science solutions into products. Continuously evaluate and improve the performance of existing models and algorithms. Stay updated with the latest advancements in AI/ML and propose innovative solutions to enhance the company's capabilities. Qualifications: Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 5-8 years' experience. Minimum of 2 years of experience in leading a team of junior Data Scientist. Should have been involved in end-to-end delivery of the scalable, optimized and enterprise AI solutions. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Practical hands-on fine-tuning/transfer learning/optimization of the Transformer architecture based Deep Learning models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Deployment of the ML models on the Kubernetes clusters Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems. Understanding of big data technologies like Hadoop, Spark, and Hive. Strong knowledge of statistical methods and experimental design. Experience with MLOps practices for CI/CD in machine learning. Strong project management skills, with the ability to manage multiple projects simultaneously. Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders. Interested candidates, please send their resumes to iqbal.kaur@birdeye.com Regards Iqbal kaur Show more Show less

Title: Senior Data Scientist (NLP) Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP) Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Qualifications: Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 5 years' experience. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Practical hands-on fine-tuning/transfer learning/optimization of the Transformer architecture-based Deep Learning models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Deployment of the ML models on the Kubernetes clusters Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems. Interested candidates, please send their resumes to iqbal.kaur@birdeye.com Regards Iqbal kaur Show more Show less

Job Description The Global Data Insights and Analytics (GDI&A) department at Ford Motors Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization. The goal of GDI&A is to drive evidence-based decision making by providing insights from data. Applications for GDI&A include, but are not limited to, Connected Vehicle, Smart Mobility, Advanced Operations, Manufacturing, Supply chain, Logistics, and Quality Analytics. Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Responsibilities Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Qualifications Minimum Qualifications Bachelor’s degree in Data science, computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 3+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or QlikSense. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Computer Science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Google, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills. Show more Show less

Bosch Software Engineering, Data Science Pune, Maharashtra, India Posted on May 28, 2025 Apply now Company Description Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 28,200+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region. Job Description Roles & Responsibilities : Roles & Responsibilities Education and Work Experience Requirements: 5 to 8 years of experience as Data Scientist 2 to 3 years of experience in Generative AI solution development Strong understanding of AI agent collaboration, negotiation, and autonomous decision-making. Experience in developing and deploying AI agents that operate independently or collaboratively in complex environments. Deep knowledge of agentic AI principles, including self-improving, self-organizing, and goal-driven agents. Proficiency in multi-agent frameworks such as AutoGen, LangGraph, LangChain, and CrewAI for orchestrating AI workflows. Hands-on experience integrating LLMs (GPT, LLaMA, Mistral, etc.) with agentic frameworks to enhance automation and reasoning. Expertise in hierarchical agent frameworks, distributed agent coordination, and decentralized AI governance. Strong grasp of memory architectures, tool use, and action planning within AI agents. Autonomy Score: Measures the degree of independence in decision-making. Collaboration Efficiency: Evaluates the ability of agents to work together and share information. Task Completion Rate: Tracks the percentage of tasks successfully executed by agents. Response Time: Measures the latency in agent decision-making and execution. Adaptability Index: Assesses how well agents adjust to dynamic changes in the environment. Resource Utilization Efficiency: Evaluates computational and memory usage for optimization. Explainability & Interpretability Score: Ensures transparency in agent reasoning and outputs. Error Rate & Recovery Time: Tracks failures and the system’s ability to self-correct. Knowledge Retention & Utilization: Measures how effectively agents recall and apply information. Hands-on experience with LLMs such as GPT, BERT, LLaMA, Mistral, Claude, Gemini, etc. Proven expertise in both open-source (LLaMA, Gemma, Mixtral) and closed-source (OpenAI GPT, Azure OpenAI, Claude, Gemini) LLMs. Advanced skills in prompt engineering, tuning, retrieval-augmented generation (RAG), reinforcement learning (RAFT), and LLM fine-tuning (PEFT, LoRA, QLoRA). Strong understanding of small language models (SLMs) like Phi-3 and BERT, along with Transformer architectures. Experience working with text-to-image models such as Stable Diffusion, DALL·E, and Midjourney. Proficiency in vector databases such as Pinecone, Qdrant for knowledge retrieval in agentic AI systems. Deep understanding of Human-Machine Interaction (HMI) frameworks within cloud and on-prem environments. Strong grasp of deep learning architectures, including CNNs, RNNs, Transformers, GANs, and VAEs. Expertise in Python, R, TensorFlow, Keras, and PyTorch. Hands-on experience with NLP tools and libraries: OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Knowledge Graphs, and LLM-based applications. Proficiency in advanced statistical methods and transformer-based text processing. Experience in reinforcement learning and planning techniques for autonomous agent behavior. Mandatory Skills Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models. Strong understanding of LLMs, and associated technologies like RAG, Agents, VectorDB and Guardrails Hand-on experience in GenAI frameworks like LlamaIndex, Langchain, Autogen, etc. Experience in cloud services like Azure, GCP and AWS Multi-agent frameworks: AutoGen, LangGraph, LangChain, CrewAI Large Language Models (LLMs): GPT, Qualifications Educational qualification: BE,BTECH or PHD Experience 7-11 years Mandatory/requires Skills : AI Preferred Skills Apply now See more open positions at Bosch Show more Show less

CSQ326R28 The Machine Learning (ML) Practice team is a highly specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as put those pipelines into production. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. The Impact You Will Have Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation Build, scale, and optimize customer data science workloads and apply best in class MLOps to productionize these workloads across a variety of domains Advise data teams on various data science such as architecture, tooling, and best practices Present at conferences such as Data+AI Summit Provide technical mentorship to the larger ML SME community in Databricks Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap What We Look For Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI 4+ years of hands-on industry data science experience, leveraging machine learning and data science tools including pandas, scikit-learn, gensim, nltk, and TensorFlow/PyTorch Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration, life-long learning, and driving business value through ML About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. Show more Show less

Bold is seeking for newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required Job Description ABOUT THIS TEAM The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL. The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology. WHAT YOU’LL DO Demonstrate ability to work on data science projects involving NLP, large language models, predictive modelling, statistical analysis, vector space modelling, machine learning etc. Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience Collaborates effectively with cross functional teams to deliver end-to-end products & features. Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. Estimates efforts, identify risks, devises and meets project schedules. Runs review meetings effectively and drive the closure of all open issues on time Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. Rises above detail to see broader issues and implications for whole product/team. WHAT YOU’LL NEED Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods Expert knowledge in Python. Experience in using large language models. Fine-tuning knowledge is good to have. Experience in feature selection, building and optimising classifiers. Experience working with backend technologies such as Flask/ Gunicorn etc. Experience on working with open source library such Spacy,NLTK,Gensim etc Experience on working with deep-learning library such as Tensor flow, Pytorch etc Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. Be a keen learner and enthusiastic about developing software. WHAT'S GOOD TO HAVE Experience with Cloud infrastructure and platforms (Azure, AWS) Experience using tools to deploy models into the production environment such as Jenkins EXPERIENCE- Module Lead- 5.5 years+ BENEFITS Outstanding Compensation Competitive salary Tax-friendly compensation structure Bi-annual bonus Annual Appraisal Equity in company 100% Full Health Benefits Group Mediclaim, personal accident, & term life insurance Group Mediclaim benefit (including parents' coverage) Practo Plus health membership for employees and family Personal accident and term life insurance coverage Flexible Time Away 24 days paid leaves Declared fixed holidays Paternity and maternity leave Compassionate and marriage leave Covid leave (up to 7 days) ADDITIONAL BENEFITS Internet and home office reimbursement In-office catered lunch, meals, and snacks Certification policy Cab pick-up and drop-off facility About BOLD We Transform Work Lives As an established global organization, BOLD helps people find jobs. Our story is one of growth, success, and professional fulfillment. We create digital products that have empowered millions of people in 180 countries to build stronger resumes, cover letters, and CVs. The result of our work helps people interview confidently, finding the right job in less time. Our employees are experts, learners, contributors, and creatives. We Celebrate And Promote Diversity And Inclusion We value our position as an Equal Opportunity Employer. We hire based on qualifications, merit, and our business needs. We don't discriminate regarding race, color, religion, gender, pregnancy, national origin or citizenship, ancestry, age, physical or mental disability, veteran status, sexual orientation, gender identity or expression, marital status, genetic information, or any other applicable characteristic protected by law. Show more Show less