Machine Learning Engineer

Data Engineer 

Responsibilities:

 

• Designing and implementing fine-tuned production ready data/ML pipelines in Hadoop platform.
• Driving optimization, testing and tooling to improve quality.
• Reviewing and approving high level & amp; detailed design to ensure that the solution delivers to the business needs and aligns to the data & analytics architecture principles and roadmap.
• Understanding business requirements and solution design to develop and implement solutions that adhere to big data architectural guidelines and address business requirements.
• Following proper SDLC (Code review, sprint process).
• Identifying, designing, and implementing internal process improvements: automating manual processes, optimizing data delivery, etc.
• Building robust and scalable data infrastructure (both batch processing and real-time) to support needs from internal and external users.
• Understanding various data security standards and using secure data security tools to apply and adhere to the required data controls for user access in the Hadoop platform.
• Supporting and contributing to development guidelines and standards for data ingestion.
• Working with a data scientist and business analytics team to assist in data ingestion and data related technical issues.
• Designing and documenting the development & deployment flow.

 

Requirements:

 

• Experience in developing rest API services using one of the Scala frameworks.
• Ability to troubleshoot and optimize complex queries on the Spark platform
• Expert in building and optimizing ‘big data’ data/ML pipelines, architectures and data sets.
• Knowledge in modelling unstructured to structured data design.
• Experience in Big Data access and storage techniques.
• Experience in doing cost estimation based on the design and development.
• Excellent debugging skills for the technical stack mentioned above which even includes analyzing server logs and application logs.
• Highly organized, self-motivated, proactive, and ability to propose best design solutions.
• Good time management and multitasking skills to work to deadlines by working independently and as a part of a team.

Job roles and responsibilities:

• Design, develop, test, deploy, maintain and improve ML models/infrastructure and software that uses these models
• Experience writing software in one or more languages such as Python, Scala, R, or similar with strong competencies in data structures, algorithms, and software design
• Experience working with recommendation engines, data pipelines, or distributed machine learning
• Experience working with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano)
• Knowledge of data analytics concepts, including bigdata, data warehouse technical architectures, ETL and reporting/analytic tools and environments
• Participate in cutting edge research in artificial intelligence and machine learning applications
• Contribute to engineering efforts from planning and organization to execution and delivery to solve complex, real world engineering problems
• Working knowledge on different Algorithms and Machine Learning techniques like, Linear & Logistic Regression analysis, Segmentation, Decisions trees, Cluster analysis and factor analysis, Time Series Analysis, K-Nearest Neighbour, K-Means algorithm, Random Forests Algorithm, NLP (Natural language processing), Sentimental analysis, various Artificial Neural Networks, Convolution Neural Nets (CNN), Bidirectional Recurrent Neural Networks (BRNN)
• Demonstrated excellent communication, presentation, and problem-solving skills

Technical Skills Required:

• GCP Native AI/ML services like Vision, NLP, Document AI, Dialogflow, CCAI, BQ etc.,
• Proficiency with a deep learning framework such as TensorFlow or Keras, etc.,
• Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas, jupyter notebook
• Expertise in visualizing and manipulating big datasets
• Ability to select hardware to run an ML model with the required latency
• Good to have MLOps and Kubeflow knowledge
• GCP ML Engineer Certification

The Biostrap platform extracts many metrics related to health, sleep, and activity.  Many algorithms are designed through research and often based on scientific literature, and in some cases they are augmented with or entirely designed using machine learning techniques.  Biostrap is seeking a Data Scientist to design, develop, and implement algorithms to improve existing metrics and measure new ones. 

As a Data Scientist at Biostrap, you will take on projects to improve or develop algorithms to measure health metrics, including:

• Research: search literature for starting points of the algorithm
• Design: decide on the general idea of the algorithm, in particular whether to use machine learning, mathematical techniques, or something else.
• Implement: program the algorithm in Python, and help deploy it.  

The algorithms and their implementation will have to be accurate, efficient, and well-documented.

• A Master’s degree in a computational field, with a strong mathematical background. 
• Strong knowledge of, and experience with, different machine learning techniques, including their theoretical background.  
• Strong experience with Python
• Experience with Keras/TensorFlow, and preferably also with RNNs
• Experience with AWS or similar services for data pipelining and machine learning.  
• Ability and drive to work independently on an open problem.
• Fluency in English.

4+ year experience in advanced analytics, model building, statistical modeling,
• Solid technical / data-mining skills and ability to work with large volumes of data; extract
and manipulate large datasets using common tools such as Python and SQL other
programming/scripting languages to translate data into business decisions/results
• Be data-driven and outcome-focused
• Must have good business judgment with demonstrated ability to think creatively and
strategically
• Must be an intuitive, organized analytical thinker, with the ability to perform detailed
analysis
• Takes personal ownership; Self-starter; Ability to drive projects with minimal guidance
and focus on high impact work
• Learns continuously; Seeks out knowledge, ideas and feedback.
• Looks for opportunities to build owns skills, knowledge and expertise.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG,
HIVE)
• Experience in risk and credit score domains preferred
• Comfortable with ambiguity and frequent context-switching in a fast-paced
environment

Position summary
As an experienced Data Scientist you’ll join a team of data scientists, analysts, and software engineers
working to push the boundaries of data science in health care. We like to experiment, iterate, and
innovate with technology, from developing new algorithms specific to health care’s challenges, to
bringing the latest machine learning practices and applications developed in other industries into the
health care world. We know that algorithms are only valuable when powered by the right data, so we
focus on fully understanding the problems we need to solve, and truly understanding the data behind
them before launching into solutions – ensuring that the solutions we do land on are impactful and
powerful

Essential functions
• Research, conceptualize, and implement analytical approaches and predictive modeling to
evaluate scenarios, predict utilization and clinical outcomes, and recommend actions to impact
results.
• Manage and execute on the entire model development process, including scope definition,
hypothesis formation, data cleaning and preparation, feature selection, model implementation
in production, validation and iteration, using multiple data sources.
• Provide guidance on necessary data and software infrastructure capabilities to deliver a scalable
solution across partners and support the implementation of the team’s algorithms and models

• Contribute to the development and publication in major journals, conferences showcasing
 leadership in healthcare data science.
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT teams and
Business stakeholders spread out across various locations in US and India to achieve business
goals
• Provide guidance to other Data Scientist and Machine Learning Engineers

Job Description

Want to make every line of code count? Tired of being a small cog in a big machine? Like a fast-paced environment where stuff get DONE? Wanna grow with a fast-growing company (both career and compensation)? Like to wear different hats? Join ThinkDeeply in our mission to create and apply Enterprise-Grade AI for all types of applications.

 

Seeking an M.L. Engineer with high aptitude toward development. Will also consider coders with high aptitude in M.L. Years of experience is important but we are also looking for interest and aptitude. As part of the early engineering team, you will have a chance to make a measurable impact in future of Thinkdeeply as well as having a significant amount of responsibility.

 

Experience

10+ Years

 

Location

Bozeman/Hyderabad

 

Skills

Required Skills:

Bachelors/Masters or Phd in Computer Science or related industry experience

3+ years of Industry Experience in Deep Learning Frameworks in PyTorch or TensorFlow

7+ Years of industry experience in scripting languages such as Python, R.

7+ years in software development doing at least some level of Researching / POCs, Prototyping, Productizing, Process improvement, Large-data processing / performance computing

Familiar with non-neural network methods such as Bayesian, SVM, Adaboost, Random Forests etc

Some experience in setting up large scale training data pipelines.

Some experience in using Cloud services such as AWS, GCP, Azure

Desired Skills:

Experience in building deep learning models for Computer Vision and Natural Language Processing domains

Experience in productionizing/serving machine learning in industry setting

Understand the principles of developing cloud native applications

 

Responsibilities

 

Collect, Organize and Process data pipelines for developing ML models

Research and develop novel prototypes for customers

Train, implement and evaluate shippable machine learning models

Deploy and iterate improvements of ML Models through feedback

Description Does solving complex business problems and real world challenges interest you Do you enjoy seeing the impact your contributions make on a daily basis Are you passionate about using data analytics to provide game changing solutions to the Global 2000 clients Do you thrive in a dynamic work environment that constantly pushes you to be the best you can be and more Are you ready to work with smart colleagues who drive for excellence in everything they do If you possess a solutions mindset, strong analytical skills, and commitment to be part of a tremendous journey, come join our growing, global team. See what Saama can do for your career and for your journey. Position: Data Scientist (2255) Location: Hinjewadi Phase 1, Pune Type: Permanent Full time Responsibilities: Work on small and large data sets of structured, semi-structured, and unstructured data to discover hidden knowledge about the client s business and develop methods to leverage that knowledge for their business. Identify and solve business challenges working closely with cross-functional teams, such as Delivery, Business Consulting, Engineering and Product Management. Develop prescriptive and predictive statistical, behavioral or other models via machine learning and/ or traditional statistical modeling techniques, and understand which type of model applies best in a given business situation. Drive the collection of new data and the refinement of existing data sources. Analyze and interpret the results of product experiments. Provide input for engineering and product teams as they develop and support our internal data platform to support ongoing statistical analyses. Requirements: Candidates should demonstrate following expertize- Must have Direct Hands-on, 7 years of experience, building complex systems using any Statistical Programming Language (R / Python / SAS) Must have fundamental knowledge of Inferential Statistics Should have worked on Predictive Modelling Experience should include the following, o File I/ O, Data Harmonization, Data Exploration o Multi-Dimensional Array Processing o Simulation & Optimization Techinques o Machine Learning Techniques (Supervised, Unsupervised) o Artificial Intelligence and Deep Learning o Natural Language Processing o Model Ensembling Techniques o Documenting Reproducible Research o Building Interactive Applications to demonstrate Data Science Use Cases Prior experience in Healthcare Domain, is a plus Experience using Big Data, is a plus. Exposure to SPARK is desirable Should have Excellent Analytical, Problem Solving ability. Should be able to grasp new concepts quickly Should be well familiar with Agile Project Management Methodology Should have experience of managing multiple simultaneous projects Should have played a team lead role Should have excellent written and verbal communication skills Should be a team player with open mind Impact on the business: Plays an important role in making Saama s Solutions game changers for our strategic partners by using data science to solve core, complex business challenges. Key relationships: Sales & pre-sales Product management Engineering Client organization: account management & delivery Saama Competencies: INTEGRITY: we do the right things. INNOVATION: we change the game. TRANSPARENCY: we communicate openly COLLABORATION: we work as one team PROBLEM-SOLVING: we solve core, complex business challenges ENJOY & CELEBRATE: we have fun Competencies: Self-starter who gets results with minimal support and direction in a fast-paced environment. Takes initiative; challenges the status quo to drive change. Learns quickly; takes smart risks to experiment and learn. Works well with others; builds trust and maintains credibility. Planful: identifies and confirms key requirements in dynamic environments; anticipates tasks and contingencies. Communicates effectively; productive communication with clients and all key stakeholders communication in both verbal and written communication. Stays the course despite challenges & setbacks. Works well under pressure. Strong analytical skills; able to apply inductive and deductive thinking to generate solutions for complex problems

• Exposure to Deep Learning, Neural Networks, or related fields and a strong interest and desire to pursue them. • Experience in Natural Language Processing, Computer Vision, Machine Learning or Machine Intelligence (Artificial Intelligence). • Programming experience in Python. • Knowledge of machine learning frameworks like Tensorflow. • Experience with software version control systems like Github. • Understands the concept of Big Data like Hadoop, MongoDB, Apache Spark