PyTorch Jobs in Gurugram.
All active PyTorch roles based in Gurugram.
Pick a job to read the details
Tap any role on the left — its description and apply link will open here.
Manager, Data Science
Share this job
About Inizio Ignite
We are Inizio Ignite, the global advisory partner for health and life sciences encompassing connected expertise across Research Partnership, Putnam, STEM, and Vynamic. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – helping healthcare leaders shape strategy and drive meaningful change.
About the Role
We are seeking an experienced Data Science Manager to join our team at Inizio Ignite. The ideal candidate will bring deep machine learning expertise, strong GenAI and cloud competencies, and hands-on experience delivering analytical solutions that drive meaningful business impact for life sciences clients.
This leader will manage data scientists, oversee project delivery, partner with cross-functional teams, and shape the development of innovative AI/ML solutions.
What you'll be doing
Leadership & Delivery
- Lead and manage a team of data scientists, providing technical guidance, mentorship, and performance oversight.
- Own end-to-end delivery of data science and GenAI engagements for pharma/biotech clients.
- Translate business problems into analytical frameworks and ensure high-quality, timely project execution.
- Drive adoption of AI/ML capabilities across client engagements and internal initiatives.
Technical Responsibilities
- Architect, design, and review ML, statistical, and GenAI solutions, ensuring scalability, accuracy, and alignment with business objectives.
- Oversee the development, validation, and deployment of predictive models, NLP pipelines, and GenAI-based applications (e.g., summarization, insights automation, generative workflows).
- Lead cloud-based solution deployment (AWS, Azure, or GCP) including orchestration, MLOps best practices, and integration with enterprise systems.
- Ensure adherence to model governance, compliance, and responsible AI frameworks.
What you'll need
- Extensive experience in data science or advanced analytics roles, with at least 2–3 years in a leadership or managerial capacity.
- Ideally prior experience in pharmaceutical, biotech, or healthcare consulting is mandatory.
- Strong expertise in machine learning, NLP, deep learning, and GenAI (LLMs, prompt engineering, RAG, fine-tuning, embeddings).
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP; exposure to MLOps frameworks preferred.
- Proficiency in Python, SQL, and common DS/ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain, etc.).
- Proven experience managing teams, delivering client projects, and presenting to senior stakeholders.
- Good to have understanding of pharma datasets (claims, RWE, clinical, medical insights, social data) and key use cases.
- Experience building GenAI solutions in production environments
Our Pledge
At Inizio, we value inclusivity, recognize the power of diversity, and inspire the next generation of change-makers. We are an equal opportunities employer and are committed to creating a dynamic work environment that values diversity, equity, and inclusion. We welcome all applications regardless of race, color, religion, gender identity, age, national origin, marital status, veteran status, genetic information, sexual orientation, or disability.
Artificial Intelligence
Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly align with every qualification, we encourage you to apply anyway.
Don't meet every job requirement? That's okay! Our company is dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role, but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.
Ready to apply?
Apply to Inizio Ignite
About Payoneer
Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.
By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.
Role Summary
We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.
Key Responsibilities
1 Model Design & Training
- Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
- Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
- Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
- Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
- Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.
2 Model Evaluation & Quality
- Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
- Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
- Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
- Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.
3 MLOps & Deployment
- Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
- Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
- Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
- Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.
4 Research & Innovation
- Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
- Contribute to internal knowledge sharing, technical documentation, and model cards.
- Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
- Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.
5 Collaboration & Stakeholder Management
- Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
- Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
- Participate in architecture reviews, sprint planning, and cross-functional design discussions.
Required Qualifications
1 Education
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
- Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.
2 Experience
- 4 – 6 years of professional experience in machine learning or NLP engineering.
- Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
- Demonstrable experience taking a model from dataset preparation through to production deployment.
3 Technical Skills — Core
- Programming: Python (proficient); familiarity with C++/CUDA a plus.
- Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
- NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
- Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
- Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
- Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
- Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
- Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.
4 Technical Skills — Nice to Have
- Experience with multimodal models or vision-language models (VLMs).
- Knowledge of model safety, alignment techniques, and responsible AI frameworks.
- Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
- Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.
Behavioural Competencies
- Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
- Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
- Ownership: Takes full accountability for model quality, timelines, and production reliability.
- Collaboration: Works effectively in cross-functional teams with diverse skill sets.
- Communication: Distils complex technical concepts for diverse audiences.
- Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.
The Payoneer Ways of Working
Act as our customer’s partner on the inside
Learning what they need and creating what will help them go further.
Do it. Own it.
Being fearlessly accountable in everything we do.
Continuously improve
Always striving for a higher standard than our last.
Build each other up
Helping each other grow, as professionals and people.
If this sounds like a business, a community, and a mission you want to be part of, apply today.
We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis.
Ready to apply?
Apply to Payoneer
Inovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data-driven solutions. And the momentum is building.
Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare’s greatest needs. Through our mission-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve.
Job Title: Senior Full Stack Machine Learning Engineer
About Us:
Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are looking for a talented and experienced Senior Full Stack Machine Learning Engineer to join our dynamic team.
Job Description:
- As a Senior Full Stack Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying machine learning models that drive our healthcare solutions. You will work closely with data scientists, software engineers, and product managers to build scalable and robust machine learning systems. Your expertise will help us transform healthcare data into actionable insights, ultimately improving patient care and operational efficiency.
Key Responsibilities:
- Model Development: Design, implement, and optimize machine learning models for various healthcare applications, including predictive analytics, natural language processing, and generative AI.
- End-to-End Deployment: Develop and maintain the full lifecycle of machine learning solutions, from data preprocessing and model training to deployment and monitoring in production environments.
- Data Engineering: Collaborate with data engineers to build and maintain data pipelines, ensuring the availability of high-quality data for training and inference.
- Software Development: Write clean, efficient, and maintainable code for machine learning applications, ensuring seamless integration with existing systems.
- Performance Optimization: Continuously monitor and improve the performance of machine learning models and systems, addressing issues related to scalability, latency, and accuracy.
- Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
- Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of continuous learning and innovation.
Qualifications:
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
- Experience: Minimum of 5 years of experience in machine learning, with a proven track record of deploying models in production environments.
Technical Skills:
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Proficiency in building applications leveraging generative AI technologies which includes LLM’s, prompt engineering, Vector Databases, RAG architectures and transfer learning is a plus.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
- Strong knowledge of data structures, algorithms, and software engineering best practices.
- Familiarity with big data technologies (e.g., Hadoop, Spark) and data pipeline tools (e.g., Airflow, Kafka).
- Experience with frontend and backend development, including frameworks such as React, Node.js, and Django.
Domain Knowledge: Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.
Soft Skills:
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
- Ability to work independently and as part of a team in a fast-paced environment.
What We Offer:
- Competitive salary and benefits package.
- Opportunity to work on impactful projects that improve healthcare outcomes.
- Collaborative and innovative work environment.
- Professional development and growth opportunities.
- Flexible work arrangements, including hybrid and remote options.
Join us in our mission to transform healthcare through technology! We look forward to hearing from you.
This position is not eligible for immigration sponsorship (e.g. H-1B, TN, or E-3). Applicants must be authorized to work in the United States as a condition of employment. (This is only applicable for US-based positions)
If you don’t meet every qualification listed but are excited about our mission and the work described, we encourage you to apply. Inovalon is most interested in finding the best candidate for the job, and you may be just the right person for this or other roles.
By embracing inclusion, we enhance our work environment and drive business success. Inovalon strives to provide equal opportunities to the communities where we operate and to our clients and everyone whom we serve. We endeavor to create a culture of inclusion in which our associates feel empowered to bring their full, authentic selves to work and pursue their professional goals in an equitable setting. We understand that by fostering this type of culture, and welcoming different perspectives, we generate innovation and growth.
Inovalon is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirement.
To review the legal requirements, including all labor law posters, please visit this link
To review the California Consumer Privacy Statement: Disclosures for California Residents, please visit this link
Ready to apply?
Apply to Inovalon
Inovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data-driven solutions. And the momentum is building.
Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare’s greatest needs. Through our mission-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve.
About Us:
Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes.
Role overview
As an MLOps Engineer, you will design, build, and operate the infrastructure and tooling that power end-to-end ML workflows on AWS, including SageMaker, Bedrock, and Snowflake Cortex. You will partner closely with data scientists, ML engineers, and platform teams to ensure models are reliable, secure, and scalable in production.
Key responsibilities
- Design, implement, and maintain CI/CD pipelines for ML models and data workflows using AWS-native services and infrastructure-as-code.
- Operationalize models built on SageMaker, Bedrock, and Snowflake Cortex, including feature pipelines, training, batch/real-time inference, and monitoring.
- Build and manage data pipelines and feature stores using services such as AWS Glue, Lambda, Step Functions, and Snowflake.
- Implement observability for ML systems (logging, metrics, tracing, drift/quality monitoring) and establish SLOs/SLAs for production ML services.
- Automate environment provisioning, configuration, and dependency management across dev, test, and production.
- Partner with security and compliance teams to ensure ML workloads meet healthcare, privacy, and regulatory standards (e.g., HIPAA).
- Collaborate with ML engineers and data scientists to productionize notebooks and prototypes into robust, maintainable services.
- Contribute to best practices, standards, and documentation for ML platform and operations across the organization.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- 4+ years of experience in software engineering, data engineering, or ML engineering with at least 2+ years focused on MLOps or ML platform work.
- Strong proficiency with Python and experience integrating ML libraries or frameworks (e.g., scikit-learn, TensorFlow, PyTorch) into production workflows.
- Hands-on expertise with AWS services relevant to MLOps: SageMaker, Bedrock, IAM, CloudWatch, ECR, ECS/EKS or Lambda, S3, Step Functions, and Glue.
- Experience with Snowflake (including Snowflake Cortex), SQL, and building secure, performant data pipelines into and out of Snowflake.
- Proficiency with CI/CD tools (e.g., GitHub Actions, GitLab CI, CodePipeline) and infrastructure-as-code (e.g., Terraform, CloudFormation, CDK).
- Familiarity with containerization and orchestration (Docker, Kubernetes) and event streaming tools (e.g., Kafka) is a plus.
- Knowledge of software engineering best practices, including testing, code reviews, version control, and design for reliability and scalability.
- Experience in regulated domains or with healthcare data standards and regulations is a plus (e.g., HIPAA, FHIR, HL7).
Soft skills and benefits
- Excellent problem-solving and analytical skills with a focus on reliability and automation.
- Strong communication and collaboration abilities, including working cross-functionally with engineering, data science, and product teams.
- Ability to work independently in a fast-paced environment
- Competitive salary and benefits package.
- Opportunity to work on impactful ML platforms that improve healthcare outcomes.
- Collaborative, innovative environment with professional development and growth opportunities.
This position is not eligible for immigration sponsorship (e.g. H-1B, TN, or E-3). Applicants must be authorized to work in the United States as a condition of employment. (This is only applicable for US-based positions)
If you don’t meet every qualification listed but are excited about our mission and the work described, we encourage you to apply. Inovalon is most interested in finding the best candidate for the job, and you may be just the right person for this or other roles.
By embracing inclusion, we enhance our work environment and drive business success. Inovalon strives to provide equal opportunities to the communities where we operate and to our clients and everyone whom we serve. We endeavor to create a culture of inclusion in which our associates feel empowered to bring their full, authentic selves to work and pursue their professional goals in an equitable setting. We understand that by fostering this type of culture, and welcoming different perspectives, we generate innovation and growth.
Inovalon is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirement.
To review the legal requirements, including all labor law posters, please visit this link
To review the California Consumer Privacy Statement: Disclosures for California Residents, please visit this link
Ready to apply?
Apply to Inovalon
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.
Key Responsibilities
- Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
- Develop and productionize ML models, taking them from prototype to scalable, live systems.
- Construct and manage the data pipelines required for model training, validation, and inference.
- Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
- Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
- Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
- Optimize applications for speed, scalability, and reliability.
- Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.
Required Qualifications
- Expert (10+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
- Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
- Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
- Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
- Data manipulation and analysis: Pandas, NumPy.
- Core ML frameworks: scikit-learn.
- Deep learning frameworks: Experience with TensorFlow or PyTorch.
- Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
- Experience with version control (Git) and CI/CD practices.
- Excellent problem-solving skills and the ability to write efficient, production-ready code.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
- Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
- Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
- Knowledge of large-scale data processing frameworks like Spark or Dask.
What Makes This Role Exciting
This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.
Key Responsibilities
- Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
- Develop and productionize ML models, taking them from prototype to scalable, live systems.
- Construct and manage the data pipelines required for model training, validation, and inference.
- Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
- Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
- Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
- Optimize applications for speed, scalability, and reliability.
- Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.
Required Qualifications
- Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
- Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
- Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
- Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
- Data manipulation and analysis: Pandas, NumPy.
- Core ML frameworks: scikit-learn.
- Deep learning frameworks: Experience with TensorFlow or PyTorch.
- Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
- Experience with version control (Git) and CI/CD practices.
- Excellent problem-solving skills and the ability to write efficient, production-ready code.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
- Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
- Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
- Knowledge of large-scale data processing frameworks like Spark or Dask.
What Makes This Role Exciting
This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
We're seeking a versatile GenAI Software Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.
Key Responsibilities
- Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments
- Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering, RAG implementation
- Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language
- Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics
- Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations
- Optimize model inference pipelines for performance, cost, and scalability in production environments
- Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour
- Collaborate with data scientists to productionize ML models and forecasting algorithms
- Write comprehensive tests including unit tests, integration tests, and prompt regression suites
- Participate in code reviews, technical design discussions, and knowledge-sharing sessions
- Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption
Required Qualifications
- 3+ years of software engineering experience with 2+ years of understanding on ML/AI systems.
- Strong programming skills in Python including understanding of ML frameworks (PyTorch, TensorFlow, Transformers)
- Understanding or experience of building and deploying LLM-powered applications in production
- Understanding or experience of front-end development with React, TypeScript, and modern web technologies
- Understanding of RESTful API design, microservices architecture, and cloud infrastructure
- Experience with prompt engineering, RAG systems
- Understanding of ML fundamentals including NLP, time-series analysis, or recommender systems
- Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
- Excellent problem-solving skills and attention to detail
- Bachelor’s degree in computer science, Machine Learning, or related field
Preferred Qualifications
- Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar)
- Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
- Experience with model serving frameworks (vLLM, TensorRT, Ray)
- Background in forecasting, planning, or analytics applications
- Familiarity with Anaplan or similar enterprise planning platforms
- Experience with A/B testing and experimentation frameworks for AI features
- Contributions to open-source ML projects or research publications
- Experience with model observability tools (LangSmith, W&B, MLflow)
What Makes This Role Exciting
- Lead a greenfield team building transformative AI capabilities from the ground up
- Work on cutting-edge conversational and agentic AI technologies
- Build user-facing AI features that directly impact how businesses plan and make decisions
- Experiment with the latest GenAI models and techniques
- Collaborate with talented engineers, data scientists, and product designers
- Solve unique challenges at the intersection of AI and enterprise software
- Grow your skills in both ML engineering and full-stack development
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.
Key Responsibilities
- Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
- Develop and productionize ML models, taking them from prototype to scalable, live systems.
- Construct and manage the data pipelines required for model training, validation, and inference.
- Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
- Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
- Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
- Optimize applications for speed, scalability, and reliability.
- Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.
Required Qualifications
- Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
- Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
- Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
- Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
- Data manipulation and analysis: Pandas, NumPy.
- Core ML frameworks: scikit-learn.
- Deep learning frameworks: Experience with TensorFlow or PyTorch.
- Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
- Experience with version control (Git) and CI/CD practices.
- Excellent problem-solving skills and the ability to write efficient, production-ready code.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
- Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
- Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
- Knowledge of large-scale data processing frameworks like Spark or Dask.
What Makes This Role Exciting
This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanInovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data-driven solutions. And the momentum is building.
Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare’s greatest needs. Through our mission-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve.
About Us:
Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are seeking a highly skilled Senior Machine Learning SDET to ensure the quality, reliability, and safety of our ML-powered healthcare products.
Job Description:
As a Senior Machine Learning SDET, you will be responsible for designing, implementing, and maintaining robust testing frameworks and quality strategies for machine learning systems across their entire lifecycle. You will collaborate closely with data scientists, ML engineers, software engineers, and product managers to validate models, data pipelines, and ML-driven services in production environments. Your work will help ensure that our ML solutions are accurate, performant, secure, and compliant with healthcare standards, ultimately improving patient care and operational efficiency.
Key Responsibilities:
- Test Strategy for ML Systems: Define and own the end-to-end test strategy for ML models, data pipelines, and services, including functional, performance, regression, and reliability testing.
- ML Model Validation: Design automated tests to validate model behavior (e.g., accuracy, drift detection, bias, stability, and robustness) across training, staging, and production environments.
- Data Quality & Pipeline Testing: Build automated tests and monitoring for data pipelines to ensure schema integrity, data completeness, data freshness, and correctness for training and inference.
- Test Automation Frameworks: Develop and maintain scalable test automation frameworks and tools for APIs, microservices, and ML workflows, integrating them into CI/CD pipelines.
- Performance & Scalability: Design and execute load and performance tests for ML inference services and batch jobs, focusing on latency, throughput, and resource utilization.
- Monitoring & Observability: Collaborate with ML and platform engineers to implement monitoring, logging, and alerting for ML systems, including model performance and data drift.
- Shift-Left Quality: Embed quality practices early in the ML development lifecycle, including testable model design, test data generation, and automated validation in CI.
- Tooling & Infrastructure: Leverage and extend existing tools (e.g., Python test frameworks, cloud services, containerization, big data tools) to support robust ML testing.
- Collaboration: Work closely with cross-functional teams to understand business and regulatory requirements and translate them into verifiable test scenarios and acceptance criteria.
- Mentorship: Provide guidance and mentorship to engineers on best practices for testing ML and data-intensive systems, fostering a culture of quality and continuous improvement.
Qualifications:
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field; Ph.D. is a plus.
- Experience: Minimum of 5 years of experience in software test engineering or SDET roles, with at least 3 years focused on testing machine learning, data, or distributed backend systems in production.
Technical Skills:
- Strong proficiency in Python and testing frameworks such as pytest, unittest, or similar, with experience testing ML code and data pipelines.
- Hands-on experience with ML libraries and ecosystems (e.g., TensorFlow, PyTorch, scikit-learn) sufficient to design model validation and testing strategies.
- Hands-on experience with generative AI concepts (LLMs, RAG, vector databases, prompt engineering, and transfer learning) and their testing implications is a strong plus.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization/orchestration (Docker, Kubernetes) for deploying and testing ML services.
- Strong knowledge of data structures, algorithms, and software engineering best practices, including code reviews, version control, and CI/CD.
- Experience building and integrating automated tests for REST/gRPC APIs and microservices, including contract and integration testing.
- Experience with performance and load testing tools and techniques for backend and ML inference services.
- Experience with observability and monitoring tools (e.g., Prometheus, Grafana, ELK, or cloud-native equivalents) for tracking model and system health.
Domain Knowledge:
- Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.
- Experience testing systems in regulated, high-compliance, or safety-critical environments is highly desirable.
Soft Skills:
- Excellent problem-solving and analytical skills, with a strong focus on edge cases, failure modes, and risk assessment.
- Strong communication and collaboration abilities, with comfort working across ML, data, product, and platform teams.
- Ability to work independently and as part of a team in a fast-paced environment, balancing quality, speed, and pragmatism.
What We Offer:
- Competitive salary and benefits package.
- Opportunity to work on impactful ML-driven healthcare products that improve patient outcomes and operational efficiency.
- Collaborative and innovative work environment.
- Professional development and growth opportunities in ML quality engineering and SDET leadership.
- Flexible work arrangements, including hybrid and remote options.
Join us in ensuring that cutting-edge AI and machine learning solutions are not only powerful but also safe, reliable, and trustworthy in healthcare. We look forward to hearing from you.
This position is not eligible for immigration sponsorship (e.g. H-1B, TN, or E-3). Applicants must be authorized to work in the United States as a condition of employment. (This is only applicable for US-based positions)
If you don’t meet every qualification listed but are excited about our mission and the work described, we encourage you to apply. Inovalon is most interested in finding the best candidate for the job, and you may be just the right person for this or other roles.
By embracing inclusion, we enhance our work environment and drive business success. Inovalon strives to provide equal opportunities to the communities where we operate and to our clients and everyone whom we serve. We endeavor to create a culture of inclusion in which our associates feel empowered to bring their full, authentic selves to work and pursue their professional goals in an equitable setting. We understand that by fostering this type of culture, and welcoming different perspectives, we generate innovation and growth.
Inovalon is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirement.
To review the legal requirements, including all labor law posters, please visit this link
To review the California Consumer Privacy Statement: Disclosures for California Residents, please visit this link
Ready to apply?
Apply to Inovalon
Staff Machine Learning Engineer
Share this job
About AiDASH
AiDASH is an enterprise AI company and the leading provider of vegetation risk intelligence for electric utilities. Powered by proprietary VegetationAI™ technology, AiDASH delivers a unified remote grid inspection and monitoring platform that uses a SatelliteFirst approach to identify and address vegetation and other threats to the grid. With a prevention-first strategy to mitigate wildfire risk and minimize storm impacts, AiDASH helps more than 140 utilities reduce costs, improve reliability, and lower liability across their networks. AiDASH exists to safeguard critical utility infrastructure and secure the future of humanAIty™. Learn more at www.aidash.com.
We are a Series C growth company backed by leading investors, including Shell Ventures, National Grid Partners, G2 Venture Partners, Duke Energy, Edison International, Lightrock, Marubeni, among others. We have been recognized by Forbes two years in a row as one of “America’s Best Startup Employers.” We are also proud to be one of the few software companies in Time Magazine’s “America’s Top GreenTech Companies 2024”. Deloitte Technology Fast 500™ recently ranked us at No. 12 among San Francisco Bay Area companies, and No. 59 overall in their selection of the top 500 for 2024.
Join us in Securing Tomorrow!
The Role
We’re looking for a seasoned Staff Machine Learning Engineer to shape and scale the backbone of our production ML ecosystem. In this role, you will architect high-performing ML systems that power our geospatial intelligence platform, transforming large-scale satellite and aerial imagery into actionable insights. You’ll lead end-to-end ownership—from model deployment and MLOps to infrastructure design—while partnering closely with data science, platform engineering, and product teams to deliver reliable, scalable, and cost-efficient ML solutions. If you thrive at the intersection of deep technical expertise, system design, and cross-functional collaboration, this role is for you.
How you'll make an impact:
ML System Architecture & Production Deployment
- Design, build, and maintain end-to-end ML pipelines for batch processing of satellite and aerial imagery
- Deploy and scale ML models in production on AWS infrastructure, leveraging services like SageMaker, Bedrock,or custom-built solutions
- Implement MLflow for experiment tracking, model versioning, and model registry management
- Architect batch inference systems optimized for throughput and cost-efficiency
- Work with geospatial data formats and coordinate reference systems
- Collaborate with data scientists to transition models from research to production
- Partner with platform engineering to build scalable compute, GPU clusters, and storage layers
ML Operations & Reliability
- Implement comprehensive model monitoring systems to track performance degradation and data drift
- Design and execute canary deployments and A/B testing frameworks for safe model rollouts
- Build active learning pipelines to continuously improve model performance with minimal labeling effort
- Establish model evaluation frameworks and performance benchmarking processesCreate alerting and observability systems for production ML workloads
Technical Leadership
- Mentor ML engineers and data scientists on best practices for production ML
- Drive technical decision-making on ML infrastructure and tooling
- Collaborate with platform and data engineering teams to optimize the ML stack
- Establish engineering standards and contribute to architectural roadmaps
What we’re looking for:
- 5+ years of experience in machine learning engineering with 2+ years in a senior or lead capacity
- Proven track record deploying and maintaining ML systems in production using AWS services (SageMaker,Lambda, ECS/EKS, S3, etc.)
- Strong hands-on experience with tools like MLflow, WandB, or similar for experiment tracking and model management
- Deep expertise in image segmentation and computer vision techniques using frameworks like PyTorch or TensorFlow
- Production experience with ensemble models (xgboost, lightgbm, RF)
ML Operations Expertise
- Experience implementing model monitoring, drift detection, and alerting systems
- Hands-on experience with canary deployments, A/B testing and Shadow deployments for ML models
- Knowledge of active learning strategies and human-in-the-loop ML systems
- Strong understanding of model evaluation metrics, bias detection, and performance analysis
Technical Skills
- Expert-level Python programming with ML libraries (scikit-learn, PyTorch/TensorFlow, NumPy, pandas, etc)
- Experience with distributed batch processing frameworks (Airflow, Step Functions, Argo Workflows, Spark,Dask, Ray or similar)
- Proficiency with AWS ML ecosystem and infrastructure-as-code (Terraform, CloudFormation)
- Hands-on experience with dataset versioning tools such as DVC, LakeFS, Delta Lake, Quilt, or Pachyderm
- Strong software engineering fundamentals: unit/integration testing, CI/CD, version control, observability, designpatterns
- Experience with containerization (Docker, Kubernetes) for model deployment
- Good to have experience with ML Orchestration tools like Kubeflow, Vertex AI, etc
- Nice to have experience with GPUs: scheduling GPU jobs, optimizing GPU performance, memory profiling
We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.
Read our Privacy Policy here: https://www.aidash.com/policy/privacy-policy/
Ready to apply?
Apply to AiDASH, Inc.