Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

 IIAD / SAD / LAD Artificial Intelligence Engineer

Senior AI Engineer

Senior QA Automation Engineer

Business Intelligence Developer

Dot Net Engineer

Engineering Manager

Staff Engineer - AI/ML

Principal Applied Data Scientist

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Dashboard Design and Development: Design, develop, and maintain interactive and user-friendly dashboards in PowerBI and Looker, focusing on clarity, performance, and data accuracy.&nbsp;</li><li>Data Lake Integration: Connect to and leverage data from various data lake sources on GCP, ensuring seamless data flow for visualization purposes.&nbsp;</li><li>Semantic Model Development: Develop and maintain robust semantic models in Looker (LookML) and PowerBI, ensuring data consistency, accuracy, and ease of use for reporting and analysis. This includes defining dimensions, measures, relationships, and calculations.&nbsp;</li><li>Machine Learning and GenAI Visualization: Create compelling visualizations to effectively communicate the results, performance, and insights derived from machine learning models and GenAI applications. This may involve visualizing model predictions, feature importance, natural language processing outputs, and other relevant data.&nbsp;</li><li>GCP Expertise: Utilize your strong understanding of GCP services to access, process, and prepare data for visualization. This may involve working with services such as BigQuery, Cloud Storage, and potentially data engineering pipelines built on GCP.&nbsp;</li><li>Collaboration: Partner closely with data scientists, data engineers, product managers, and business stakeholders to understand their data visualization needs and translate them into effective visual solutions.&nbsp;</li><li>Requirements Gathering: Elicit and document visualization requirements from various stakeholders, ensuring alignment with business objectives.&nbsp;</li><li>Performance Optimization: Optimize dashboard and visualization performance to ensure fast load times and efficient data rendering.&nbsp;</li><li>Data Quality Assurance: Ensure the accuracy, consistency, and reliability of data presented in visualizations.&nbsp;</li><li>Best Practices and Standards: Establish and enforce data visualization best practices and standards across the organization.&nbsp;</li><li>Training and Support: Provide guidance and support to other team members on data visualization tools and techniques.&nbsp;</li><li>Continuous Learning: Stay up to date with the latest trends and advancements in data visualization, PowerBI, Looker, GCP, and related technologies, particularly in the context of AI/ML.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s or master’s degree in computer science, Data Science, Statistics, Information Systems, or a related field.&nbsp;</li><li>Minimum of 3 years of experience as a Visualization Expert, Data Visualization Engineer, or a similar role.&nbsp;</li><li>Proven expertise in designing and developing interactive dashboards and reports using PowerBI and Looker.&nbsp;</li><li>Strong experience in connecting to and working with data lakes, preferably on the Google Cloud Platform (GCP).&nbsp;</li><li>Solid understanding and hands-on experience in developing semantic models, particularly with LookML in Looker and data modeling within PowerBI.&nbsp;</li><li>Preferable experience in creating visualizations specifically for machine learning and GenAI applications, understanding the nuances of presenting model outputs and insights.&nbsp;</li><li>Proficiency in SQL for data extraction and manipulation.&nbsp;</li><li>Familiarity with data warehousing concepts and data modeling techniques.&nbsp;</li><li>Experience with data preparation, ELT (preferred) / ETL processes.&nbsp;</li><li>Strong analytical and problem-solving skills with the ability to interpret complex data.&nbsp;</li><li>Excellent communication and presentation skills, with the ability to convey technical information to both technical and non-technical audiences.&nbsp;&nbsp;</li><li>Ability to work independently and collaboratively in a fast-paced environment.&nbsp;&nbsp;</li><li>Strong portfolio showcasing your data visualization skills and experience.&nbsp;</li></ul>

Responsibilities: Agentic AI Development:&nbsp;&nbsp; <ul><li>Design, build, and deploy agentic AI systems using frameworks such as LangChain, Lang Graph, and related libraries.&nbsp;&nbsp;</li><li>Develop and deploy multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.&nbsp;</li></ul> RAG Pipelines:&nbsp; <ul><li>Implement and optimize retrieval-augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.&nbsp;</li></ul> LLM Engineering:&nbsp; <ul><li>Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning, and dynamic adaptation.&nbsp;</li><li>Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.&nbsp;</li></ul> Enterprise AI Platform:&nbsp; <ul><li>Lead the development of enterprise-grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.&nbsp;</li><li>Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.&nbsp;</li></ul> MLOps &amp; Observability:&nbsp; <ul><li>Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.&nbsp;</li><li>Applied AI Prototyping:&nbsp;</li></ul> Rapidly prototype, experiment, and iterate to improve AI agent capabilities.&nbsp; Collaboration &amp; Research:&nbsp; <ul><li>Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings.&nbsp;</li><li>Collaborate effectively with other engineers, researchers, and data scientists.&nbsp;</li><li>Contribute to the documentation and standardization of technical code and practices.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related quantitative field. Master’s or Ph.D. is a strong plus.&nbsp;</li><li>5+ years overall experience in software development, data science, or machine learning.&nbsp;</li><li>1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.&nbsp;</li><li>1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.&nbsp;</li></ul>

Responsibilities: <ul><li>Design, develop, and implement systems leveraging Large Language Models (LLMs) for various applications.</li><li>Prepare data, fine-tune models, and build data, analytics and ML Pipelines to support</li><li>Collaborate with business partners and key stakeholders to understand their needs and present insights and solutions.</li><li>Build innovative AI solutions tailored to business requirements.</li><li>Utilize cloud technologies in Azure and/or AWS for deploying and managing AI models and solutions.</li><li>Communicate complex technical concepts and results to non-technical audiences effectively.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools</li><li>Lead the design and development of solutions using Agentic AI</li></ul> Requirements: Basic Qualifications: <ul><li>Bachelor’s or Master’s in Computer Science, Mathematics, Statistics, or a related field.</li><li>8+ years of experience in software engineering, data science, AI, or a related field.</li><li>Proficiency in software development and statistical analysis.</li><li>Experience with Large Language Models and their applications.</li><li>Strong communication skills and the ability to present technical results to business stakeholders.</li><li>Experience with solution architecting and design.</li><li>Hands-on experience with cloud platforms such as Azure and/or AWS.</li><li>Proficiency in programming languages such as Python, R, or similar.</li><li>Strong problem-solving skills and the ability to work independently as well as part of a team.</li></ul> Preferred Qualifications: <ul><li>Experience with large language models and supporting workflows.</li><li>History of project leadership and development.</li><li>Familiarity with Agile development.</li><li>Experience in applications on sales, marketing, and market research.</li><li>Design, develop, and implement systems leveraging Large Language Models (LLMs) for various applications.</li><li>Prepare data, fine-tune models, and build data, analytics and ML Pipelines to support.</li><li>Collaborate with business partners and key stakeholders to understand their needs and present insights and solutions.</li><li>Build innovative AI solutions tailored to business requirements.</li><li>Utilize cloud technologies in Azure and/or AWS for deploying and managing AI models and solutions.</li><li>Communicate complex technical concepts and results to non-technical audiences effectively.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools.</li><li>Lead the design and development of solutions using Agentic AI.</li></ul>

Responsibilities: <ul><li>Together with the team of developers handle the product quality.</li><li>Lead and manage the automation testing efforts and deliverables.</li><li>Plan and prioritize testing activities.</li><li>Maintain and improve an existing test automation framework.</li><li>Develop automation tests for API and UI.</li><li>Execute, maintain and update automation tests.</li><li>Review and analyze tests execution results.</li><li>Maintain all related test documentation.</li><li>Prepare testing data.</li><li>Proactively acquire and clarify requirements as necessary.</li><li>Mentor less skilled teammates and newcomers.</li></ul> Requirements: <ul><li>Strong knowledge of OOP (understanding OOP in automation).</li><li>Excellent knowledge of automation testing principles.</li><li>Excellent knowledge of web-based application structure.</li><li>Excellent knowledge of Python programming language.</li><li>Expert in REST API testing.</li><li>Experience in UI testing.</li><li>Wide experience in developing automation testing frameworks.</li></ul>

Responsibilities: <ul><li>Client is seeking a skilled Business Intelligence Developer to design, build, and maintain enterprise-scale data products and data sources using platforms like Tableau and Streamlit.</li><li>The ideal candidate will be a detail-oriented developer with strong technical skills who can translate business requirements into robust analytical solutions.</li><li>This role requires a mixture of business acumen and technical expertise, along with an ability to build strong partnerships and collaborate to solve problems.</li><li>Design, develop, and maintain interactive data products and reports in Tableau, Streamlit, and other BI tools.</li><li>Build and optimize data sources, ensuring data integrity and performance at enterprise scale</li><li>Collaborate with business stakeholders to gather requirements and translate them into technical specifications.</li><li>Develop scalable data product solutions that can accommodate growing user bases and data volumes.</li><li>Implement best practices for data product design, data modeling, and visualization techniques.</li><li>Monitor data product performance and user adoption, making improvements as needed.</li><li>Maintain documentation for data products, data sources, and development processes.</li><li>Troubleshoot and resolve technical issues with existing data products and data connections.</li><li>Support data governance initiatives by ensuring consistent data definitions and calculations across reports.</li><li>Participate in code reviews and maintain version control for BI development projects.</li><li>Stay current with BI tool updates and emerging visualization technologies.</li><li>Provide technical support to end users and assist with data product-related questions.</li><li>Contribute to the development of reusable components and templates for efficiency gains.</li></ul> Requirements: Qualifications <ul><li>3+ years in the data space as an analyst, engineer, or equivalent.</li><li>3+ years experience designing, implementing, operating, and extending enterprise dimensional models.</li><li>3+ years working with a large-scale data warehouse, preferably in a cloud environment.</li><li>3+ years of hands-on experience developing data products and reports in Tableau, including advanced calculations, parameters, and complex visualizations.</li><li>Experience with Streamlit or similar Python-based data product frameworks.</li><li>Experience with modern data stack technologies including cloud data warehouses (AWS/Snowflake) and ELT tools.</li><li>1+ years maintaining a project workstream to identify tasks, milestones, and deliverables.</li><li>Bachelors degree in Computer Science, Information Systems, Mathematics,</li></ul>

Responsibilities: <ul><li>Act as a technical guide on one or more applications utilized by company.</li><li>Work with the Business System Analyst to ensure designs satisfy functional requirements.</li><li>Work with large, complex data sets and high throughput data pipelines that meet business requirements.</li><li>Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.</li><li>Build data and analytics tools that utilize the data pipeline to provide actionable insights to operational efficiency and other key business&nbsp;performance metrics.</li><li>Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs.</li><li>Collaborate with data scientists and architects on several projects.</li><li>Solve various complex problems</li></ul> Requirements: <ul><li>Minimum of 4 years of related experience</li><li>Bachelors degree preferred or equivalent experience</li></ul>

Job Summary: <ul><li>R&amp;D Team builds world-class SaaS solutions for industrial customers for their asset and network device management.&nbsp;</li><li>As a part of the high-performing engineering team, the engineering manager will build and maintain a software development team tasked to deliver high-quality software that delights our customers.&nbsp;</li><li>He/She will report to Senior Engineering Manager.</li></ul> Responsibilities: <ul><li>As a software engineering manager of a Cloud-based Platform, be both a highly technical, hands-on coder and an effective resource manager.</li><li>Communicate across functions and other stakeholders and drive engineering initiatives</li><li>Introduce and maintain AGILE SDLC best practices in the team.</li><li>Participate in Code Review, Technical design discussion&nbsp;</li><li>Be a subject matter expert in the Public Cloud and On-Prem based Data Platform</li><li>Define and influence product strategy</li></ul> Requirements:﻿ <ul><li>10+ years of software engineering work experience, including hands-on technical management.</li><li>In-depth knowledge on NMS and other network software</li><li>7+ years’ experience coding in one of the following languages: Go and Python.</li><li>Experience with Docker and Kubernetes for deployment and orchestration.</li><li>Hands-on knowledge on Public Cloud Services and infrastructure.</li><li>7+ years’ of demonstrated experience recruiting and managing technical teams, including performance management</li></ul>

Role Description: <ul><li>As a Staff Engineer, you will play a pivotal role in shaping the future of Gen AI at our client by defining technical strategy, overseeing complex machine learning architectures, and ensuring seamless integration of Gen AI solutions into our platform and applications at scale.</li><li>You will mentor and guide a small engineering team while providing expertise in state-of-the-art AI/ML practices, ensuring a robust production pipeline and the professional management of models.&nbsp;</li></ul> Responsibilities: <ul><li>Help lead the technical strategy and execution for AI projects across the organization.</li><li>Designing, deploying, and managing the lifecycle of AI/ML models, including retraining and monitoring for continuous improvement within our solution.</li><li>Designing and driving Gen AI features on peta-byte scale datasets Driving innovation in NLP and other ML solutions, ensuring alignment with our client business goals. Architecting, developing and overseeing scalable, production-ready AI systems.</li><li>Providing technical mentorship to the AI/ML engineering team, fostering growth and collaboration.</li><li>Conducting in-depth research and staying abreast of advancements in Gen AI and deep learning technologies.</li><li>Collaborating with cross-functional teams, including Product, to evaluate business requirements and determine optimal AI solutions.</li><li>Reviewing code, offering best practices, and ensuring the delivery of high-quality solutions.&nbsp;</li><li>Representing our client technical excellence through publications, presentations, and participation in industry events.</li><li>Opportunity to work on cutting-edge AI projects at scale.</li></ul> Requirements: <ul><li>8+ years experience in managing large-scale datasets and distributed computing environments, with a preference for Google Cloud Platform expertise.</li><li>Java programming experience.</li><li>Experience with integration and deployment of AI/ML into production at scale within a SaaS solution.</li><li>Demonstrates independent thinking, capable of analyzing unique challenges, overcoming technical hurdles and delivering impactful AI solutions.</li><li>Hands-on experience with Generative AI techniques, including RAG pipelines, LLM fine-tuning, prompt engineering, and diffusion models.</li><li>Strong knowledge of generative AI frameworks and tools, such as Hugging Face, LangChain, or OpenAI APIs.</li><li>Experience in developing and scaling Generative AI solutions for NLP, vision, or multimodal tasks.</li><li>Advanced knowledge of modern AI frameworks, such as PyTorch, TensorFlow/Keras, Hugging Face Transformers, and JAX/Flax.</li><li>Expertise in Python, Docker, Kubernetes, and Helm.</li><li>Excellent communication skills, particularly in mentoring, knowledge sharing, and cross-team collaboration.</li><li>Willingness to be in office 3 days per week.</li></ul>

Role Description: <ul><li>Develop and own the data science roadmap that aligns with our client business goals.</li><li>Define success metrics and oversee the entire lifecycle of data initiatives from concept to production deployment.</li><li>Architect, develop, and deploy state-of-the-art machine learning models.</li><li>Champion best practices in model development, validation, and monitoring in production environments.</li><li>Partner with product, engineering, and business teams to translate business requirements into data-driven solutions.</li></ul> Responsibilities: <ul><li>Provide technical leadership and mentor the data science team.</li><li>Provide technical leadership and mentor the data science team.</li><li>Architect and provide production monitoring and support for our client ML services.</li><li>Stay ahead of industry trends by continuously evaluating emerging technologies and methodologies in data science and machine learning.</li><li>Represent our client technical excellence through publications, presentations, and participation in industry events.</li></ul> Requirements: <ul><li>10+ years of professional experience in data science with a proven track record in building and supporting production grade ML systems.</li><li>Must be highly proficient in Python with hands-on experience in machine learning frameworks (e.g., TensorFlow, PyTorch).</li><li>Experience working with large-scale datasets and distributed computing platforms like GCP.</li><li>Strong understanding of ML lifecycle and MLOps practices.</li><li>Experience with monitoring tools like Prometheus, Grafana and logging systems e.g. ELK stack.</li></ul>

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30 python Jobs found

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

IIAD / SAD / LAD Artificial Intelligence Engineer

Senior AI Engineer

Senior QA Automation Engineer

Business Intelligence Developer

Dot Net Engineer

Engineering Manager

Staff Engineer - AI/ML

Principal Applied Data Scientist

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30 python Jobs found

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

IIAD / SAD / LAD Artificial Intelligence Engineer

Senior AI Engineer

Senior QA Automation Engineer

Business Intelligence Developer

Dot Net Engineer

Engineering Manager

Staff Engineer - AI/ML

Principal Applied Data Scientist

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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WhiteCrow is on a mission to connect companies with the best talent across the globe.