66 Mlops Tools Jobs - Page 2

As a Data Solutions Architect at Apple, your role will involve bridging the gap between AI capabilities and real-world business challenges within the global supply chain function. You will drive automation, resilience, and efficiency across the value chain by implementing cutting-edge Generative AI and Agentic AI solutions tailored for supply chain use cases. Your responsibilities will include designing, building, and deploying AI solutions, leveraging technologies like LLMs, autonomous agents, reinforcement learning, and reasoning frameworks. You will lead the experimentation and operationalization of AI agents across planning, sourcing, logistics, and fulfillment domains. Additionally, you will architect scalable data pipelines, ensuring robust data integration from ERP, Supply Chain systems, and third-party APIs. Implementing MLOps best practices to manage the AI lifecycle will also be a key aspect of your role. Your domain expertise in supply chain processes such as planning, logistics, procurement, and manufacturing will be essential in working closely with cross-functional supply chain IT and operations teams to translate business challenges into AI-driven solutions. You will drive continuous improvement through digital twin models, predictive analytics, and scenario simulation. Collaborating with data scientists and engineers in a fast-paced agile environment, you will act as a thought leader in identifying high-value opportunities for AI within the enterprise supply chain. Your ability to present technical concepts and business value to executive stakeholders clearly and persuasively will be crucial in this role. Minimum Qualifications: - Bachelors or Masters in Computer Science, Data Science, Operations Research, or a related field. - 10+ years of experience in data engineering, AI/ML, or analytics roles. - 4+ years of hands-on experience with Generative AI and Agent-based architectures. - Strong background in data engineering: SQL, Spark, Python, Airflow, cloud platforms, and data lakes. - Deep understanding of supply chain processes. Preferred Qualifications: - Experience with commercial supply chain platforms. - Exposure to digital twin and simulation platforms. - Strong storytelling, communication, and stakeholder management skills. - Experience in building and leading cross-functional project teams. If you meet the qualifications and are enthusiastic about revolutionizing the supply chain industry with innovative AI solutions, we invite you to submit your CV for consideration.,

As an established global provider of business process and technology management services, Sutherland offers a wide range of analytics-driven solutions to support the entire customer lifecycle. With over 30 years of experience, we have been helping customers across various industries achieve greater agility through transformed and automated customer experiences. We are currently looking for a skilled and delivery-focused AI Manager (L5) to lead the development and implementation of AI solutions under the guidance of the AI Architect. In this role, you will be responsible for managing cross-functional teams of AI developers, data scientists, and MLOps engineers to build scalable, production-grade AI systems including Generative AI, Agentic AI, and Transformer-based models. Your responsibilities will include managing day-to-day execution of AI projects, ensuring timely delivery, quality, and alignment to architectural design. You will lead AI developers and collaborate closely with data scientists, BAs, and MLOps engineers to build end-to-end AI workflows. Additionally, you will translate architectural blueprints into executable components, prototypes, and production-ready services. You will oversee the development of GenAI applications, RAG pipelines, and agent-based solutions using frameworks like LangChain and LangGraph. Supervising the integration of AI services with business systems and ensuring model outputs are usable, interpretable, and reliable will also be part of your role. Monitoring project KPIs, technical progress, and resource allocation, and escalating risks and blockers as needed will be essential. You will review code, support reusable component development, and enforce engineering best practices. Moreover, coaching and mentoring junior engineers and analysts within the AI team will also be expected from you. To qualify for this role, you should have at least 7 years of experience in AI/ML engineering or software development, with 2-3 years in team leadership roles. Experience delivering projects using GenAI, LLMs, or Transformer models is required. A solid understanding of prompt engineering, APIs, data preprocessing, and model integration is essential. Hands-on coding proficiency in Python and familiarity with ML libraries (PyTorch, HuggingFace, LangChain, etc.) is necessary. Exposure to vector databases and RAG architectures for enterprise knowledge retrieval is beneficial. Strong organizational, problem-solving, and team leadership skills are a must. A Bachelors or Masters degree in computer science, AI, or related technical field is preferred. Preferred skills for this role include experience working in agile delivery environments with CI/CD pipelines and MLOps tools, familiarity with multi-agent orchestration platforms, LLMOps, or auto-evaluation frameworks, prior experience in AI delivery within telecom, BFSI, healthcare, or manufacturing domains, and the ability to interface with business stakeholders to gather requirements and validate outcomes.,

JOB DESCRIPTION Job Summary: We are seeking a skilled and experienced SeniorAI Engineerwith 5+ years of hands-on experience in designing, developing, and deploying AI/ML solutions. You will work closely with the AI Architect to build scalable models, optimize infrastructure, and integrate AI systems into production environments. This role offers the opportunity to work on cutting-edge technologies including LLMs, MLOps, intelligent automation, and cloud-native AI deployments. Key Responsibilities: Design, develop, and deploy AI/ML models using Python and frameworks like TensorFlow, PyTorch, or scikit-learn. Support the implementation and fine-tuning of transformer-based models and LLMs (e.g., GPT, BERT). Build and maintain data pipelines and model training workflows. Collaborate with the AI Architect to integrate models into automation frameworks (e.g., Appium) and enterprise systems. Containerize AI applications using Docker and orchestrate with Kubernetes. Contribute to CI/CD pipelines and GitOps workflows for AI model deployment. Monitor model performance and assist in retraining and optimization. Document model architectures, training processes, and deployment steps. Stay updated with the latest AI tools, libraries, and best practices. Work closely with cross-functional teams to deliver AI components aligned with business goals. Required Qualifications: Bachelor's or master's degree in computer science, Data Science, Engineering, or related field. 5+ years of professional experience in AI/ML development. Proficiency in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, Hugging Face). Experience with LLMs and transformer architectures. Familiarity with Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP). Understanding of CI/CD and GitOps practices. Experience with Appium for intelligent automation and testing. Exposure to MLOps tools and practices. Preferred Qualifications : Experience working in AI/ML environments or supporting data science teams. Knowledge of distributed systems and performance optimization. Experience in embedded software development is a strong plus. Certifications in AI, cloud, or DevOps technologies. Soft Skills: Strong analytical and problem-solving skills. Effective communication and documentation abilities. Ability to work independently and collaboratively in a team. Eagerness to learn and grow under technical mentorship. Organized and detail-oriented with a proactive mindset. EXPERTISE AND QUALIFICATIONS: AI Engineer

About Us: Senior Data Scientist - Kotak811 Kotak811 is a Neobank incubated by Kotak Mahindra Bank, with a view of providing completely digitized banking services in the convenience of the customer's mobile phone. 811 is an early mover in the Indian fintech space that started off as a downloadable savings bank account in 2017, post demonetization, when India took one step closer to a digital economy. The Senior Data Scientist in Bangalore (or Mumbai) will be part of the 811 Data Strategy Group that comprises Data Engineers, Data Scientists and Data Analytics professionals. He/she will be associated with one of the key functional areas such as Product Strategy, Cross Sell, Asset Risk, Fraud Risk, Customer Experience etc. and help build robust and scalable solutions that are deployed for real time or near real time consumption and integrated into our proprietary Customer Data Platform (CDP). This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the growth trajectory of a super fast evolving digital product. Key Requirements of The Role . Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space . 4 - 8 Years of relevant experience in the space . Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product and business teams . Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets . Create great data stories with expertise in robust EDA and statistical inference. Experience in Experimentation design a big plus but should understands fundamentals of A/B testing . Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch, Caffe is a big plus . Experience with analytical programming languages, tools and libraries (Python a must) as well as Shell scripting . Very proficient is SQL and other relational databases. Proficient in PySpark. Experience in using NoSQL databases. Candidate who is able to handle unstructured data with ease preferred . Experience in working with AWS/Azure/GCP ecosystems. MLOps tools experience a plus . Good understanding of programming best practices and building code artifacts for reuse. Should be comfortable with version controlling and collaborate comfortably in tools like git . Ability to create frameworks that can perform model RCAs using analytical and interpretability tools. Should be able to peer review model documentations/code bases and find opportunities . Experience in end-to-end delivery of AI driven Solutions (Deep learning , traditional data science projects) a big plus . Strong communication, partnership and teamwork skills . Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision . A self-starter who is looking to build grounds up and contribute to the making of a potential big name in the space . Experience in Banking and financial services is a plus. However, sound logical reasoning and first principles problem solving are even more critical A typical day in the life of the job role: 1. As a key partner at the table, attend key meetings with the business team to bring in the data perspective to the discussions 2. Perform comprehensive data explorations around to generate inquisitive insights and scope out the problem 3. Develop simplistic to advanced solutions to address the problem at hand. We believe in making swift (albeit sometimes marginal) impact to business KPIs and hence adopt an MVP approach to solution development 4. Build re-usable code analytical frameworks to address commonly occurring business questions 5. Perform 360-degree customer profiling and opportunity analyses to guide new product strategy. This is a nascent business and hence opportunities to guide business strategy are plenty 6. Guide team members on data science and analytics best practices to help them overcome bottlenecks and challenges 7. The role will be an approximate 60% IC - 40% leading and the ratios can vary basis need and fit 8. Develop Customer-360 Features that will be integrated into the Customer Data Platform (CDP) to enhance the single view of our customer Website: https://www.kotak811.com/

About Astro 247: Astro 247 is an AI-powered astrology app that provides users with instant insights into their future. Our mission is to blend technology with ancient wisdom, offering a unique and engaging astrology experience. We are looking for a passionate AI Engineer Intern to join our growing team. This role is ideal for students or fresh graduates who are eager to apply their knowledge of AI/ML in a fast-paced, product-driven environment. This is a full-time, in-office internship based in Bangalore . Remote applicants will not be considered Responsibilities Research, design, and prototype AI/ML models for natural language understanding, recommendation systems, and conversational AI. Work on LLM fine-tuning, embeddings, prompt optimization, and dialogue design for astrology-based use cases. Collaborate with product and engineering teams to deploy scalable AI features into production. Analyze user interactions and feedback to continuously improve model accuracy and performance. Explore new techniques in Generative AI, text classification, and personalization to enhance the user experience. Requirements Pursuing or recently completed Bachelors/Masters in Computer Science, AI, Data Science, or related field. Strong foundation in Python, machine learning frameworks (PyTorch/TensorFlow), and NLP libraries (Transformers, LangChain, OpenAI API, etc.). Familiarity with LLMs, embeddings, vector databases, and conversational AI systems. Good problem-solving skills and ability to work independently in a startup environment. Bonus: Experience with MLOps tools, cloud platforms (AWS/GCP), or prior projects in chatbots/GenAI. What Youll Gain Competitive stipend for the internship Hands-on experience building and deploying real-world AI systems at scale. Mentorship from senior engineers and product leaders. Exposure to cutting-edge LLM, GenAI, and personalization techniques . Potential to transition into a full-time AI Engineer role after internship. Please send us your resume or portfolio/GitHub, and a short note to [HIDDEN TEXT] Show more Show less

As a Senior Data Scientist AI, you will lead the design and development of machine learning and generative AI models that enhance our platform. You will work closely with engineers, product managers, and cybersecurity SMEs to innovate how we analyze architectures, assess risks, and automate threat intelligence. This is a hands-on, highly strategic role that requires both technical depth and product insight. Key Responsibilities Design and implement ML and NLP models for use in analysis, pattern recognition, and AI-powered automation. Build and evaluate generative AI models (e.g., LLMs or RAG pipelines) to automate threat model generation and risk recommendations. Collaborate with product and engineering to align AI solutions with customer pain points and business goals. Conduct data discovery, wrangle large security and architecture datasets, and ensure data quality for training and inference. Lead experiments, performance tuning, and model deployment using MLOps best practices. Develop reusable components and contribute to internal AI frameworks and libraries. Interpret and communicate complex data science results to non-technical stakeholders. Mentor junior data scientists and help define the future AI roadmap at ThreatModeler. Required Qualifications 5+ years of industry experience in data science, machine learning, or AI development, preferably in enterprise software or cybersecurity. Advanced degree (MS or PhD) in Computer Science, Data Science, Statistics, or a related field. Strong experience in NLP, LLMs (e.g., OpenAI, Cohere, Anthropic), and transformer architectures. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face). Deep understanding of model evaluation, bias/fairness, data preprocessing, and statistical analysis. Familiarity with cloud environments (AWS/GCP/Azure) and containerized model deployment (Docker, Kubernetes). Experience working with graph-based models, threat intelligence, or security ontologies is a strong plus. Preferred Qualifications Experience with MLOps tools (MLflow, Vertex AI, SageMaker). Understanding of threat modeling methodologies Background in building SaaS AI solutions for large-scale enterprise clients.

JD_AI/ML Senior Engineer About The Role We are seeking a highly skilled and experienced AI/ML Engineer to join our dynamic team at Medibuddy dedicated to improving healthcare services experience. In this role, you will be instrumental in designing, developing, and deploying cutting-edge artificial intelligence and machine learning solutions that directly impact patient care and operational efficiency. You will leverage your expertise in cloud platforms, large language models, and robust MLOps practices to build scalable and observable AI systems. This position requires a strong advocate for best practices and a mentor who can guide junior engineers, fostering a culture of technical excellence and continuous improvement within the healthcare domain. Responsibilities Champion and advocate for AI/ML best practices, including model governance, ethical AI, data privacy, and responsible AI development. Design, develop, and implement end-to-end AI/ML solutions, from data ingestion and model training to deployment and monitoring. Work extensively with Large Language Models (LLMs), including fine-tuning, prompt engineering, and integration into various applications. Implement comprehensive observability strategies for AI/ML systems, including logging, monitoring, alerting, and performance tracking to ensure system health and model efficacy. Architect and implement solutions for streaming existing software systems into AI/ML pipelines for real-time inference and data processing. Provide technical guidance, mentorship, and support to junior AI/ML engineers, helping them grow their skills and contribute effectively to the team. Collaborate closely with DevOps, software engineers, and product managers to translate business requirements into technical solutions. Conduct research and stay up-to-date with the latest advancements in AI/ML, cloud technologies, and industry trends. Familiarity with AWS cloud services to build, deploy, and manage scalable machine learning infrastructure and applications. Familiarity with developing and maintaining robust MLOps pipelines for continuous integration, continuous delivery (CI/CD), and automated model deployment. Qualifications Bachelor&aposs or Master&aposs degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. 5+ years of professional experience in AI/ML engineering or a similar role. Strong proficiency in Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Demonstrated experience working with Large Language Models (LLMs) and their applications. Hands-on experience with MLOps tools and practices, including CI/CD, version control (Git), and model monitoring. Expertise in setting up and maintaining observability for AI/ML systems (e.g., Prometheus, Grafana, ELK stack). Proven experience with AWS cloud services (e.g., Sagemaker, EC2, S3, Lambda, EKS) for deploying and managing ML workloads. Experience with real-time data streaming technologies (e.g., Kafka, Kinesis) and integrating them with ML pipelines. Excellent communication and interpersonal skills, with a proven ability to advocate for best practices and mentor junior team members. Strong problem-solving abilities and a keen attention to detail. Show more Show less

You are a Data Science Specialist with 4-5 years of experience in designing and implementing advanced analytical solutions. You should have a strong foundation in statistics and expertise in solving real-world business problems using Machine Learning and Data Science. Your track record should include building and deploying data products, and any exposure to NLP and Generative AI will be considered an advantage. Your key responsibilities will include collaborating with cross-functional teams to translate business problems into data science use cases, designing, developing, and deploying data science models, building and productionizing data products for measurable business impact, performing exploratory data analysis, feature engineering, model validation, and performance tuning, as well as applying statistical methods to uncover trends, anomalies, and actionable insights. You will need to implement scalable solutions using Python (or R/Scala), SQL, and modern data science libraries. It is important to stay updated with advancements in NLP and Generative AI and evaluate their relevance to internal use cases. Additionally, you should be able to communicate findings and recommendations clearly to both technical and non-technical stakeholders. Qualifications: - Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, Engineering, or a related discipline is required. - A Master's degree or certifications in Data Science, Machine Learning, or Applied Statistics is a strong advantage. Experience: - 4-5 years of hands-on experience in data science projects across different domains. - Demonstrated experience in end-to-end ML model development, from problem framing to deployment. - Prior experience working with cross-functional business teams is highly desirable. Must-Have Skills: - Statistical Expertise: Strong understanding of hypothesis testing, regression, classification techniques, and distributions. - Business Problem Solving: Ability to translate ambiguous business challenges into data science use cases. - Model Development: Hands-on experience in building and validating machine learning models. - Programming Proficiency: Strong skills in Python (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn), and SQL. - Data Manipulation: Experience in handling structured/unstructured datasets, EDA, and data cleaning. - Communication: Ability to explain technical concepts to non-technical audiences. - Version Control & Collaboration: Familiarity with Git/GitHub and collaborative practices. - Deployment Mindset: Understanding how to build usable and scalable data products. Desirable Skills: - Experience with survival analysis or time-to-event modeling techniques. - Exposure to NLP methods like tokenization, embeddings, sentiment analysis. - Familiarity with Generative AI technologies like LLMs, transformers, prompt engineering. - Experience with MLOps tools, pipeline orchestration, or cloud platforms (AWS, GCP, Azure).,

You are a senior professional with at least 6+ years of hands-on experience in Python focusing on AI technologies. Your proficiency lies in Python and you have worked with libraries such as NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch. Your expertise includes a solid understanding of machine learning algorithms, model evaluation, and data preprocessing techniques. You have experience dealing with both structured and unstructured data sets. Additionally, you are familiar with version control systems like Git and collaborative development practices. Your strong problem-solving skills enable you to work effectively both independently and as part of a team. Desired Skills: - You have experience in natural language processing (NLP), computer vision, or time-series forecasting. - You are familiar with MLOps tools and practices for model deployment and monitoring. - Your background includes working with Generative AI models such as GPT, LLaMA, or Stable Diffusion. - You have knowledge of prompt engineering, fine-tuning, or embedding techniques for large language models (LLMs). - Hands-on experience with LLM frameworks like LangChain, Haystack, or Transformers (Hugging Face) is a plus. - You understand vector databases (e.g., Postgres, Pinecone) for retrieval-augmented generation (RAG) pipelines. - Any contributions to open-source AI/ML projects or published research would be beneficial. Locations: Hyderabad / Chennai / Bangalore / Pune. If you meet the above criteria and are interested in this opportunity, please share your resume at hr@neev.global or call 9429691736. This is a full-time position that requires you to work in person.,

As a Generative AI Lead, you will be responsible for spearheading the design, development, and implementation of cutting-edge GenAI solutions within enterprise-grade applications. Your role will encompass leveraging your expertise in Large Language Models (LLMs), prompt engineering, and scalable AI system architecture, coupled with hands-on experience in MLOps, cloud technologies, and data engineering. Your primary responsibilities will include designing and deploying scalable and secure GenAI solutions utilizing LLMs such as GPT, Claude, LLaMA, or Mistral. You will lead the architecture of Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, Weaviate, FAISS, or ElasticSearch. Additionally, you will be involved in prompt engineering, evaluation frameworks, and collaborating with cross-functional teams to integrate GenAI into existing workflows and applications. Moreover, you will develop reusable GenAI modules for various functions like summarization, Q&A bots, and document chat, while leveraging cloud-native platforms such as AWS Bedrock, Azure OpenAI, and Vertex AI for deployment and optimization. You will ensure robust monitoring and observability across GenAI deployments and apply MLOps practices for CI/CD, model versioning, validation, and research into emerging GenAI trends. To be successful in this role, you must possess at least 8 years of overall AI/ML experience, with a focus of at least 3 years on LLMs/GenAI. Strong programming skills in Python and proficiency in cloud platforms like AWS, Azure, and GCP are essential. You should also have experience in designing and deploying RAG pipelines, summarization engines, and chat-based applications, along with familiarity with MLOps tools and evaluation metrics for GenAI systems. Preferred qualifications include experience with fine-tuning open-source LLMs, knowledge of multi-modal AI, familiarity with domain-specific LLMs, and a track record of published work or contributions in the GenAI field. In summary, as a Generative AI Lead, you will play a pivotal role in driving innovation and excellence in the development and deployment of advanced GenAI solutions, making a significant impact on enterprise applications and workflows.,

We are seeking a skilled and passionate Prompt Engineer with expertise in Prompt Engineering and LLM-based application development. As a Prompt Engineer, you will be responsible for designing, developing, and scaling GenAI-powered applications using cutting-edge technologies in AI, full-stack development, and cloud computing. Your key responsibilities will include designing and developing AI applications utilizing Large Language Models (LLMs) such as GPT-4, Claude, or LLaMA. You will be tasked with writing, optimizing, and evaluating prompts for various tasks and use cases. Proficiency in Python, JavaScript (React/Node.js), or other full-stack technologies is essential for this role. Additionally, you will be expected to build responsive frontend interfaces using frameworks like React.js, Vue.js, or similar. Integration with AI APIs such as OpenAI, Azure OpenAI, Cohere, etc., and working with frameworks like LangChain, LlamaIndex, and RAG pipelines will be part of your daily tasks. Implementing vector databases like Pinecone, Weaviate, and FAISS for knowledge retrieval is also crucial. Collaboration with cross-functional teams for system integration and deployment to ensure best practices in coding, testing, DevOps, and cloud deployment is a key aspect of this role. The ideal candidate should possess proficiency in Python, JavaScript (React/Node.js), or other full-stack technologies and have experience with AI/ML frameworks like TensorFlow, PyTorch, and Hugging Face. Hands-on experience with Prompt Engineering for Large Language Models (LLMs) such as GPT, Claude, LLaMA, etc., and knowledge of RAG, LangChain, or LlamaIndex are highly desired. Familiarity with AI APIs like OpenAI, Azure OpenAI, and backend development using FastAPI, Flask, or Express is required. Experience in frontend development using React or Vue.js, familiarity with CI/CD, Docker, and cloud platforms (AWS, Azure, GCP) are essential skills for this role. Preferred skills include experience with LangChain, LlamaIndex, or similar frameworks, familiarity with tools like Hugging Face, OpenAI Playground, Azure OpenAI Studio, knowledge of MLOps tools, and data pipelines, and understanding of prompt tuning and fine-tuning LLMs.,

Role: Senior AI/ML Engineer Function: Machine Learning / AI Engineering Industry: Fintech, SaaS, Artificial Intelligence About Company The client is an early-stage, venture-backed fintech using AI to simplify cash-flow analytics for high-volume B2C businesses. Its platform pairs natural-language queries with machine learning to deliver real-time insights and friction-free reconciliation. You join a small, fast-moving team that prizes ownership, experimentation, and transparent collaboration. The mission is clear: give operators instant, accurate financial visibility so they can scale with confidence. Position Overview You lead the end-to-end AI charter that powers financial automation, intelligent reconciliation, and anomaly detection. You shape the GenAI roadmap, productionize cutting-edge ML systems, and build a world-class teamall while delivering reliable, compliant, and low-latency solutions for transactional finance. Role & Responsibilities Define the AI and GenAI vision for reconciliation, document understanding, financial classification, and payment behavior intelligence. Translate product problems into scalable ML systems and GenAI workflows. Research, experiment, and productionize LLM-based pipelines tailored to enterprise financial operations. Deploy and maintain ML and LLM pipelines in production, including observability, retries, retraining, and versioning. Implement feedback loops that continuously learn from user actions and corrections. Optimize performance and latency of GenAI systems in high-throughput transactional environments. Ensure data privacy, regulatory compliance, and explainability of AI outputs in financial contexts. Lead, hire, mentor, and grow a team of ML and GenAI engineers. Collaborate with product managers, backend engineers, and data engineers to ship AI-powered features. Evangelize responsible AI practices and an experimentation culture across the organization. Must have Criteria 5+ years in AI/ML with at least 12 years hands-on with LLMs and GenAI. Deep knowledge of ML algorithms, NLP, transformers, vector search, embeddings, classification, and unsupervised learning. Proven track record building and deploying GenAI applications using OpenAI APIs, HuggingFace, LangChain, or LlamaIndex. Strong coding skills in Python and experience with PyTorch or TensorFlow, scikit-learn, pandas, and MLOps tools such as MLflow or Airflow. Hands-on experience fine-tuning LLMs (LoRA, QLoRA, PEFT) and crafting prompts for deterministic outputs. Expertise with OCR/NLP tools for semi-structured document extraction and parsing. Ability to work with unstructured, noisy financial data at scale. End-to-end ownership of ML systems from research through deployment and monitoring. Nice to Have Familiarity with open-source LLMs like Mistral, Claude, LLaMA, or Zephyr. Experience with chunking strategies, prompt templates, and hybrid search in RAG systems. Background in enterprise SaaS or fintech domains such as banking, reconciliation, ERP, or accounting. Knowledge of graph-based ML or probabilistic models for complex transaction flows. Past experience building AI systems in an early-stage startup or as a founding team member. Fintech domain expertise. What We Offer Foundational role where you define how AI evolves at the company. High impact on real-world financial decisions requiring accuracy and auditability. Ownership of deep ML and cutting-edge GenAI problems. Product-first, collaborative culture that values high agency and technical depth. Show more Show less

As an experienced AI/ML Architect, you will play a crucial role in leading the design, development, and deployment of cutting-edge Generative AI solutions. Your deep understanding of AI/ML architectures, technical leadership skills, and expertise in cloud platforms like GCP will be instrumental in designing robust, scalable, and production-ready systems. Collaborating closely with cross-functional teams and stakeholders, you will implement state-of-the-art AI solutions that address real-world challenges and drive business value. Your responsibilities will include providing technical leadership by guiding development teams through best practices and architecture reviews. You will design end-to-end Generative AI solutions, develop data pipelines, train models, deploy solutions, and monitor them in real-time. Leveraging MLOps tools, you will automate workflows for scalable and repeatable deployments. Your role will also involve optimizing deployment pipelines using tools like Docker, Kubernetes, and cloud-native services, ensuring seamless integration into existing CI/CD pipelines. In addition, you will focus on building scalable ETL workflows, implementing data preprocessing, and feature engineering pipelines to prepare data for Generative AI applications. Identifying and implementing optimization strategies for model performance enhancement will be a key aspect of your work. You will also drive the development of Proof of Concepts (POCs) and pilot projects, collaborating with delivery and product teams to scale successful pilots to production-grade solutions. To excel in this role, you should have at least 10 years of experience in AI/ML architecture, model development, and production deployment. Your expertise in designing, implementing, and scaling Generative AI and LLM-based solutions, along with hands-on experience with frameworks like LangChain and RAG, will be invaluable. Proficiency in Python, SQL, MLOps tools, containerization, and CI/CD pipelines is essential. Your strong technical leadership, communication skills, and strategic thinking abilities will be crucial in driving the adoption of Generative AI solutions and enabling continuous improvement. Joining our team will provide you with the opportunity to work on cutting-edge AI solutions, collaborate with a technology-driven team, and drive innovation through technical leadership and mentorship. You will have access to the latest AI/ML technologies and frameworks, ensuring continuous professional growth in this dynamic field.,

Job Description: We are looking for a Lead Generative AI Engineer with 35 years of experience to spearhead development of cutting-edge AI systems involving Large Language Models (LLMs) , Vision-Language Models (VLMs) , and Computer Vision (CV) . You will lead model development, fine-tuning, and optimization for text, image, and multi-modal use cases. This is a hands-on leadership role that requires a deep understanding of transformer architectures, generative model fine-tuning, prompt engineering, and deployment in production environments. Roles and Responsibilities: Lead the design, development, and fine-tuning of LLMs for tasks such as text generation, summarization, classification, Q&A, and dialogue systems. Develop and apply Vision-Language Models (VLMs) for tasks like image captioning, VQA, multi-modal retrieval, and grounding. Work on Computer Vision tasks including image generation, detection, segmentation, and manipulation using SOTA deep learning techniques. Leverage frameworks like Transformers, Diffusion Models, and CLIP to build and fine-tune multi-modal models. Fine-tune open-source LLMs and VLMs (e.g., LLaMA, Mistral, Gemma, Qwen, MiniGPT, Kosmos, etc.) using task-specific or domain-specific datasets. Design data pipelines , model training loops, and evaluation metrics for generative and multi-modal AI tasks. Optimize model performance for inference using techniques like quantization, LoRA, and efficient transformer variants. Collaborate cross-functionally with product, backend, and ML ops teams to ship models into production. Stay current with the latest research and incorporate emerging techniques into product pipelines. Requirements: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 35 years of hands-on experience in building, training, and deploying deep learning models, especially in LLM, VLM , and/or CV domains. Strong proficiency with Python , PyTorch (or TensorFlow), and libraries like Hugging Face Transformers, OpenCV, Datasets, LangChain, etc. Deep understanding of transformer architecture , self-attention mechanisms , tokenization , embedding , and diffusion models . Experience with LoRA , PEFT , RLHF , prompt tuning , and transfer learning techniques. Experience with multi-modal datasets and fine-tuning vision-language models (e.g., BLIP, Flamingo, MiniGPT, Kosmos, etc.). Familiarity with MLOps tools , containerization (Docker), and model deployment workflows (e.g., Triton Inference Server, TorchServe). Strong problem-solving, architectural thinking, and team mentorship skills. Show more Show less

You are an exceptional and highly motivated Lead Data Scientist with experience in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field. You will spearhead the design, development, and deployment of an automotive OEMs next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. As a recognized expert in advanced forecasting methodologies, you will possess a strong foundation in data engineering and MLOps principles. You will demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. **Role & Responsibilities:** **Strategic Leadership & Application Design:** Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems. Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques. Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. **Advanced Model Development & Research:** Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques including Time Series Analysis, Machine Learning, Deep Learning, Probabilistic Forecasting, and Hierarchical & Grouped Forecasting. Incorporate diverse data sources and conduct extensive exploratory data analysis to identify patterns and key features influencing automotive forecasts. Stay abreast of the latest academic research and industry advancements in forecasting, machine learning, and AI. **Application Development & Deployment (MLOps):** Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management. Collaborate closely with cross-functional teams to ensure seamless integration, deployment, and maintenance of the application. **Performance Evaluation & Optimization:** Define and implement rigorous evaluation metrics for forecasting accuracy and business impact. Perform A/B testing and comparative analyses to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. **Collaboration & Mentorship:** Work cross-functionally with various business units to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly to technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers. **Requirements:** **Qualifications & Skills:** Education in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related field. 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role. Technical proficiency in Python, R, Machine Learning/Deep Learning Frameworks, Forecasting Specific Libraries, Data Warehousing & Big Data Technologies, Cloud Platforms, MLOps, Data Visualization, and strong analytical skills. **Preferred Qualifications:** Publications in top-tier conferences or journals, experience with real-time forecasting systems, familiarity with automotive data types, experience with distributed version control systems, and knowledge of agile development methodologies. **Soft Skills:** Exceptional communication, collaboration, intellectual curiosity, strategic thinking, mentorship, resilience, and adaptability. This role offers an unparalleled opportunity to make a significant impact on the strategic direction and operational efficiency of a global automotive leader, contributing directly to the future of intelligent manufacturing and supply chain management. If you are looking to play a pivotal role in shaping a rapidly growing venture studio, thrive in a collaborative, innovative environment, access professional development opportunities, and enjoy competitive benefits, then you may be a great fit for this position.,

As an AI Computer Vision Engineer with 4+ years of experience, you will be responsible for developing and training computer vision models for various tasks such as object detection, image classification, and face recognition. You will optimize models for performance on edge devices and apply data augmentation techniques to image/video datasets. Additionally, you will need proficiency in Large Language Models and a strong understanding of statistical analysis and machine learning algorithms. Your role will involve hands-on implementation of machine learning algorithms like linear regression, logistic regression, decision trees, and clustering algorithms. Understanding image processing concepts and experience in model optimization, quantization, or deploying to edge devices will be essential. You should have strong programming skills in Python (or C++) and expertise in implementing and optimizing machine learning pipelines for seamless integration into production systems. Experience with real-time computer vision applications, OpenCV, NumPy, PyTorch/TensorFlow, and computer vision models like YOLOv5, Mask R-CNN will be beneficial. Engaging with multiple teams, contributing to key decisions, and providing solutions that apply across multiple teams are expected from you. You will lead the implementation of large language models in AI applications and research cutting-edge AI techniques to enhance system performance. Contribution to the development and deployment of AI solutions across various domains is also part of your responsibilities. In terms of requirements, you should design, develop, and deploy ML models for OCR-based text extraction, table and line-item detection, and named entity recognition. Evaluating and integrating third-party OCR tools, developing pre-processing and post-processing pipelines for image/text data, and familiarity with video analytics platforms are necessary skills. Experience with MLOps tools, academic CV research, and knowledge of GPU acceleration or hardware integration will be advantageous for this role.,

As a Python Backend Engineer specializing in AWS with a focus on GenAI & ML, you will be responsible for designing, developing, and maintaining intelligent backend systems and AI-driven applications. Your primary objective will be to build and scale backend systems while integrating AI/ML models using Django or FastAPI. You will deploy machine learning and GenAI models with frameworks like TensorFlow, PyTorch, or Scikit-learn, and utilize Langchain for GenAI pipelines. Experience with LangGraph will be advantageous in this role. Collaboration with data scientists, DevOps, and architects is essential to integrate models into production. You will be working with AWS services such as EC2, Lambda, S3, SageMaker, and CloudFormation for infrastructure and deployment purposes. Additionally, managing CI/CD pipelines for backend and model deployments will be a key part of your responsibilities. Ensuring the performance, scalability, and security of applications in cloud environments will also fall under your purview. To be successful in this role, you should have at least 5 years of hands-on experience in Python backend development and a strong background in building RESTful APIs using Django or FastAPI. Proficiency in AWS cloud services is crucial, along with a solid understanding of ML/AI concepts and model deployment practices. Familiarity with ML libraries like TensorFlow, PyTorch, or Scikit-learn is required, as well as experience with Langchain for GenAI applications. Experience with DevOps tools such as Docker, Kubernetes, Git, Jenkins, and Terraform will be beneficial. An understanding of microservices architecture, CI/CD workflows, and agile development practices is also desirable. Nice to have skills include knowledge of LangGraph, LLMs, embeddings, and vector databases, as well as exposure to OpenAI APIs, AWS Bedrock, or similar GenAI platforms. Additionally, familiarity with MLOps tools and practices for model monitoring, versioning, and retraining will be advantageous. This is a full-time, permanent position with benefits such as health insurance and provident fund. The work location is in-person, and the schedule involves day shifts from Monday to Friday in the morning. If you are interested in this opportunity, please contact the employer at +91 9966550640.,

As a Learning Data Science/Machine Learning Professional at our organization, you will be responsible for conducting live instruction sessions to teach core topics in data science and machine learning. These topics include supervised and unsupervised learning, deep learning, model evaluation, and MLOps. You will engage with learners through interactive sessions to ensure a comprehensive understanding of the subject matter. Collaboration with content teams is a crucial aspect of this role. You will work closely with these teams to design labs, conduct code walkthroughs, and develop real-world case studies utilizing Python, scikit-learn, TensorFlow/PyTorch, and cloud-based data science and machine learning services. Your input will contribute to the creation of a dynamic and engaging curriculum. In addition to live instruction and curriculum collaboration, you will provide support to learners by addressing technical queries, debugging code, reviewing notebooks, and offering constructive feedback on assignments and projects. Your mentorship will extend to guiding learners on capstone projects such as image/video models, NLP pipelines, recommendation systems, and deployment pipelines. Continuous improvement is a key focus area of this role. You will analyze learner performance data to refine modules, introduce emerging topics like transformers and generative models, and enhance assessments to ensure an enriching learning experience. To be successful in this position, you should possess a minimum of 3 years of industry or academic experience in data science, machine learning, or artificial intelligence. A Master's degree in Data Science, Machine Learning, AI, or a Computer Science specialization in AI and Data Science/Machine Learning is required. Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch is essential. Familiarity with MLOps tools like Docker, Kubernetes, MLflow, and cloud ML services such as AWS SageMaker, GCP AI Platform, or Azure ML is highly desirable. Strong presentation and mentoring skills in live and small-group settings are crucial for this role. Previous teaching or educational technology experience would be a significant advantage in fulfilling the responsibilities of this position.,

Rockwell Automation is a global technology leader dedicated to assisting the world's manufacturers in enhancing productivity, sustainability, and agility. With over 28,000 employees striving to make a positive impact daily, we take pride in our exceptional team. Our customers, remarkable companies contributing to essential sectors such as healthcare, agriculture, and environmental conservation, inspire our team of energetic problem solvers to drive meaningful change worldwide. If you are a maker, forward thinker, or problem solver seeking a platform to showcase your skills, we invite you to consider joining us! As an AI Architect at Rockwell Automation based in Pune, Noida, or Bangalore, India, you will play a crucial role in designing, developing, and implementing enterprise-grade artificial intelligence solutions. Reporting to the Director of Enterprise Architecture, you will operate from our Pune office in a hybrid capacity. Collaborating with diverse teams including data scientists, engineers, and business leaders, you will ensure that AI systems are scalable, secure, and aligned with organizational objectives. **Your Responsibilities:** - **Architect and implement AI solutions**: Design and supervise end-to-end AI architectures that seamlessly integrate with existing IT and data infrastructure, focusing on scalability, performance, and maintainability. - **Lead cross-functional delivery teams**: Provide guidance to data scientists, engineers, and business stakeholders across the AI solution lifecycle, from ideation and prototyping to production deployment and monitoring. - **Evaluate and recommend technologies**: Assess AI/ML platforms, frameworks, and tools to ensure alignment with business requirements and technical feasibility. - **Establish best practices**: Define standards for model development, testing, deployment, and lifecycle management, ensuring compliance with ethical AI principles and data privacy regulations. - **Mentor and evangelize**: Offer technical leadership and mentorship to junior architects and data professionals, while advocating for AI adoption and architectural vision within the organization. **The Essentials You Will Have:** - A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. - 5+ years of experience in designing and implementing AI architectures in production environments. - Proficiency in AI/ML frameworks and tools such as TensorFlow, PyTorch, Keras, and cloud-based AI services. - Strong programming skills in Python, R, Java, or similar languages. - Deep understanding of data structures, algorithms, and software engineering best practices. - Experience leading complex AI projects with cross-functional teams and delivering solutions that drive business outcomes. - Familiarity with ethical AI practices and data protection regulations. **The Preferred You Might Also Have:** - Experience deploying AI solutions on cloud platforms in hybrid or multi-cloud environments. - Knowledge of MLOps tools and practices for continuous integration, deployment, and monitoring of AI models. - Strong problem-solving abilities and the capacity to translate business requirements into scalable technical solutions. - Experience in mentoring and developing talent within AI or data science teams. **What We Offer:** Our benefits package includes comprehensive mindfulness programs, volunteer paid time off, employee assistance programs, personalized wellbeing programs, on-demand professional development courses, and other local benefits. At Rockwell Automation, we are committed to fostering a diverse, inclusive, and authentic workplace. If you are enthusiastic about this role but do not meet every qualification in the job description, we encourage you to apply as you might be the right fit for this position or other roles. Rockwell Automation's hybrid policy mandates employees to work at a Rockwell location at least on Mondays, Tuesdays, and Thursdays unless they have a business obligation elsewhere.,

You are an experienced Software Engineer specializing in Machine Learning with at least 2+ years of relevant experience. In this role, you will be responsible for designing, developing, and optimizing machine learning solutions and data systems. Your proven track record in implementing ML models, building scalable systems, and collaborating with cross-functional teams will be essential in solving complex challenges using data-driven approaches. As a Software Engineer - Machine Learning, your primary responsibilities will include designing and implementing end-to-end machine learning solutions, building and optimizing scalable data pipelines, collaborating with data scientists and product teams, monitoring and optimizing deployed models, staying updated with the latest trends in machine learning, debugging complex issues related to ML systems, and documenting processes for knowledge sharing and clarity. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related fields. Your technical skills should include a strong proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or scikit-learn, experience with data processing tools like Pandas, NumPy, and Spark, proficiency in SQL and database systems, hands-on experience with cloud platforms (AWS, GCP, Azure), familiarity with CI/CD pipelines and Git, and experience with model deployment frameworks like Flask, FastAPI, or Docker. Additionally, you should possess strong analytical skills, leadership abilities to guide junior team members, and a proactive approach to learning and collaboration. Preferred qualifications include experience with MLOps tools like MLflow, Kubeflow, or SageMaker, knowledge of big data technologies such as Hadoop, Spark, or Kafka, familiarity with advanced ML techniques like NLP, computer vision, or reinforcement learning, and experience in designing and managing streaming data workflows. Key Performance Indicators for this role include successfully delivering optimized and scalable ML solutions within deadlines, maintaining high model performance in production environments, and ensuring seamless integration of ML models with business applications. Join us in this exciting opportunity to drive innovation and make a significant impact in the field of Machine Learning.,

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

Job Title: Senior Python Developer AI/ML Document Automation Location: Hyderabad Work Mode: Hybrid Experience: 5+ Years Job Summary: We are looking for a highly skilled Senior Python Developer with deep expertise in AI/ML and document automation . The ideal candidate will lead the design and development of intelligent systems for extracting and processing structured and unstructured data from documents such as invoices, receipts, contracts, and PDFs. This role involves both hands-on coding and architectural contributions to scalable automation platforms. Roles and Responsibilities: Design and develop modular Python applications for document parsing and intelligent automation. Build and optimize ML/NLP pipelines for tasks like Named Entity Recognition (NER), classification, and layout-aware data extraction. Integrate rule-based and AI-driven techniques (e.g., regex, spaCy, PyMuPDF, Tesseract) to handle diverse document formats. Develop and deploy models via REST APIs using FastAPI or Flask, and containerize with Docker. Collaborate with cross-functional teams to define automation goals and data strategies. Conduct code reviews, mentor junior developers, and uphold best coding practices. Monitor model performance and implement feedback mechanisms for continuous improvement. Maintain thorough documentation of workflows, metrics, and architectural decisions. Mandatory Skills: Expert in Python (OOP, asynchronous programming, modular design). Strong foundation in machine learning algorithms and natural language processing techniques. Hands-on experience with Scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers. Proficient in developing REST APIs using FastAPI or Flask. Experience in PDF/text extraction using PyMuPDF, Tesseract, or similar tools. Skilled in regex-based extraction and rule-based NER. Familiar with Git, Docker, and any major cloud platform (AWS, GCP, or Azure). Exposure to MLOps tools such as MLflow, Airflow, or LangChain. Show more Show less

You will be responsible for designing and developing scalable AI and machine learning models to address complex business challenges. Your role will involve leading end-to-end model development, including data collection, preprocessing, training, validation, deployment, and monitoring. Collaboration with cross-functional teams, such as data engineers, software developers, and product managers, will be crucial. Additionally, you will optimize existing AI models for enhanced performance and accuracy. It is essential that you stay informed about the latest research and trends in AI/ML and assess their relevance to company products. Documenting processes, models, and code to facilitate knowledge sharing and reproducibility will be part of your responsibilities. Moreover, you will mentor junior team members and foster a culture of innovation. To qualify for this position, you should possess a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. You must have at least 5 years of experience in AI/ML, data science, or related roles. Proficiency in Python and ML frameworks like TensorFlow, PyTorch, and scikit-learn is required. A solid grasp of machine learning algorithms, data structures, and software engineering principles is essential. Experience with cloud platforms such as AWS, Azure, or GCP, as well as familiarity with MLOps tools, is preferred. Hands-on experience in NLP, computer vision, or deep learning applications is a plus. Strong problem-solving and analytical skills, along with excellent communication and collaboration abilities, are necessary for this role. While a PhD in an AI/ML-related field is not mandatory, it would be advantageous. Experience in deploying models in production environments using CI/CD pipelines is a plus. Any contributions to open-source AI/ML projects or publications in esteemed journals/conferences will be highly regarded. Please note that the above description is referenced from hirist.tech.,

You are an experienced Python Backend Engineer with a strong background in AWS and AI/ML. Your primary responsibility will be to design, develop, and maintain Python-based backend systems and AI-powered services. You will be tasked with building and managing RESTful APIs using Django or FastAPI for AI/ML model integration. Additionally, you will develop and deploy machine learning and GenAI models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Your expertise in implementing GenAI pipelines using Langchain will be crucial, and experience with LangGraph is considered a strong advantage. You will leverage various AWS services such as EC2, Lambda, S3, SageMaker, and CloudFormation for infrastructure and deployment purposes. Collaborating with data scientists, DevOps, and architects to integrate models and workflows into production will be a key aspect of your role. Furthermore, you will be responsible for building and managing CI/CD pipelines for backend and model deployments. Ensuring the performance, scalability, and security of applications in cloud environments will be paramount. Monitoring production systems, troubleshooting issues, and optimizing model and API performance will also fall under your purview. To excel in this role, you must possess at least 5 years of hands-on experience in Python backend development. Your strong experience in building RESTful APIs using Django or FastAPI is essential. Proficiency in AWS cloud services, a solid understanding of ML/AI concepts, and experience with ML libraries are prerequisites. Hands-on experience with Langchain for building GenAI applications and familiarity with DevOps tools and microservices architecture will be beneficial. Additionally, having Agile development experience and exposure to tools like Docker, Kubernetes, Git, Jenkins, Terraform, and CI/CD workflows will be advantageous. Experience with LangGraph, LLMs, embeddings, and vector databases, as well as knowledge of MLOps tools and practices, are considered nice-to-have qualifications. In summary, as a Python Backend Engineer with expertise in AWS and AI/ML, you will play a vital role in designing, developing, and maintaining intelligent backend systems and GenAI-driven applications. Your contributions will be instrumental in scaling backend systems and implementing AI/ML applications effectively.,

As a Software Engineer specializing in AI/ML/LLM/Data Science at Entra Solutions, a FinTech company within the mortgage Industry, you will play a crucial role in designing, developing, and deploying AI-driven solutions using cutting-edge technologies such as Machine Learning, NLP, and Large Language Models (LLMs). Your primary focus will be on building and optimizing retrieval-augmented generation (RAG) systems, LLM fine-tuning, and vector search technologies using Python. You will be responsible for developing scalable AI pipelines that ensure high performance and seamless integration with both cloud and on-premises environments. Additionally, this role will involve implementing MLOps best practices, optimizing AI model performance, and deploying intelligent applications. In this role, you will: - Develop, fine-tune, and deploy AI/ML models and LLM-based applications for real-world use cases. - Build and optimize retrieval-augmented generation (RAG) systems using Vector Databases such as ChromaDB, Pinecone, and FAISS. - Work on LLM fine-tuning, embeddings, and prompt engineering to enhance model performance. - Create end-to-end AI solutions with APIs using frameworks like FastAPI, Flask, or similar technologies. - Establish and maintain scalable data pipelines for training and inferencing AI models. - Deploy and manage models using MLOps best practices on cloud platforms like AWS or Azure. - Optimize AI model performance for low-latency inference and scalability. - Collaborate with cross-functional teams including Product, Engineering, and Data Science to integrate AI capabilities into applications. Qualifications: Must Have: - Proficiency in Python - Strong hands-on experience in AI/ML frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain, and OpenAI APIs. Good to Have: - Experience with LLM fine-tuning, embeddings, and transformers. - Knowledge of NLP, vector search technologies (ChromaDB, Pinecone, FAISS, Milvus). - Experience in building scalable AI models and data pipelines with Spark, Kafka, or Dask. - Familiarity with MLOps tools like Docker, Kubernetes, and CI/CD for AI models. - Hands-on experience in cloud-based AI deployment using platforms like AWS Lambda, SageMaker, GCP Vertex AI, or Azure ML. - Knowledge of prompt engineering, GPT models, or knowledge graphs. What's in it for you - Competitive Salary & Full Benefits Package - PTOs / Medical Insurance - Exposure to cutting-edge AI/LLM projects in an innovative environment - Career Growth Opportunities in AI/ML leadership - Collaborative & AI-driven work culture Entra Solutions is an equal employment opportunity employer, and we welcome applicants from diverse backgrounds. Join us and be a part of our dynamic team driving innovation in the FinTech industry.,